{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Знакомство с Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Обзор основных инструментов Python, предназначенных для подготовки и анализа данных"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### scikit-learn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Jupyter Notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### NumPy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "массив NumPy:\n",
      "[[1 2 3]\n",
      " [4 5 6]\n",
      " [7 8 9]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "x = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\n",
    "print(\"массив NumPy:\\n{}\".format(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SciPy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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T2xR5VkT8N6enOi96ybqY6p0q8ZbNP5ev5YaYKMr9sAAjzI8zVX64FK6/B292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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc0a4057f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Задаем данные для круговой диаграммы\n",
    "labels = 'Python', 'C++', 'Ruby', 'Java'\n",
    "sizes = [215, 130, 245, 210]\n",
    "colors = ['gold', 'yellowgreen', 'lightcoral', 'lightskyblue']\n",
    "# Отделяем первый сегмент\n",
    "explode = (0.1, 0, 0, 0)\n",
    " \n",
    "# Строим круговую диаграмму\n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors,\n",
    "        autopct='%1.1f%%', shadow=True, startangle=140)\n",
    " \n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Возраст</th>\n",
       "      <th>Город</th>\n",
       "      <th>Имя</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24</td>\n",
       "      <td>Москва</td>\n",
       "      <td>Ирина</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>30</td>\n",
       "      <td>Нью-Йорк</td>\n",
       "      <td>Артем</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>43</td>\n",
       "      <td>Берлин</td>\n",
       "      <td>Кирилл</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>Париж</td>\n",
       "      <td>Ольга</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Возраст     Город     Имя\n",
       "0       24    Москва   Ирина\n",
       "1       30  Нью-Йорк   Артем\n",
       "2       43    Берлин  Кирилл\n",
       "3       33     Париж   Ольга"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from IPython.display import display\n",
    "\n",
    "# Создаем простой набор данных с характеристиками пользователей\n",
    "data = {'Имя': [\"Ирина\", \"Артем\", \"Кирилл\", \"Ольга\"],\n",
    "        'Город' : [\"Москва\", \"Нью-Йорк\", \"Берлин\", \"Париж\"],\n",
    "        'Возраст' : [24, 30, 43, 33]\n",
    "       }\n",
    "\n",
    "data_pandas = pd.DataFrame(data)\n",
    "# Выводим данные\n",
    "display(data_pandas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Возраст</th>\n",
       "      <th>Город</th>\n",
       "      <th>Имя</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>43</td>\n",
       "      <td>Берлин</td>\n",
       "      <td>Кирилл</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>Париж</td>\n",
       "      <td>Ольга</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Возраст   Город     Имя\n",
       "2       43  Берлин  Кирилл\n",
       "3       33   Париж   Ольга"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Выбрать все строки, в которых значение столбца Возраст больше 30\n",
    "display(data_pandas[data_pandas.Возраст > 30])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mortgage</th>\n",
       "      <th>life_ins</th>\n",
       "      <th>cre_card</th>\n",
       "      <th>deb_card</th>\n",
       "      <th>mob_bank</th>\n",
       "      <th>curr_acc</th>\n",
       "      <th>internet</th>\n",
       "      <th>perloan</th>\n",
       "      <th>savings</th>\n",
       "      <th>atm_user</th>\n",
       "      <th>markpl</th>\n",
       "      <th>age</th>\n",
       "      <th>cus_leng</th>\n",
       "      <th>response</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>24.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>36.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mortgage  life_ins  cre_card  deb_card  mob_bank  curr_acc  internet  \\\n",
       "0         0         0         0         0         0         0         0   \n",
       "1         1         1         0         1         1         0         0   \n",
       "2         1         1         0         1         0         0         0   \n",
       "3         1         1         1         1         0         1         0   \n",
       "4         1         1         0         1         0         0         0   \n",
       "5         0         0         0         1         1         1         0   \n",
       "6         0         0         0         1         0         0         0   \n",
       "7         1         1         0         1         0         0         0   \n",
       "8         1         1         0         1         0         0         0   \n",
       "\n",
       "   perloan  savings  atm_user  markpl   age  cus_leng  response  \n",
       "0        0        0         0       0   NaN         1         0  \n",
       "1        0        0         1       0  18.0         2         1  \n",
       "2        0        0         0       1  24.0         2         1  \n",
       "3        0        0         1       1  36.0         2         1  \n",
       "4        1        0         1       0   NaN         2         0  \n",
       "5        0        0         0       0  18.0         2         1  \n",
       "6        0        0         1       0  54.0         1         1  \n",
       "7        0        0         1       0  46.0         1         1  \n",
       "8        0        0         1       1   NaN         3         0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Загружаем набор данных ResponseMissing.сsv в пандасовский датафрейм data\n",
    "data = pd.read_csv(\"C:/Trees/ResponseMissing.csv\")\n",
    "# Выводим данные\n",
    "display(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data[\"age\"].fillna(data[\"age\"].mean(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mortgage</th>\n",
       "      <th>life_ins</th>\n",
       "      <th>cre_card</th>\n",
       "      <th>deb_card</th>\n",
       "      <th>mob_bank</th>\n",
       "      <th>curr_acc</th>\n",
       "      <th>internet</th>\n",
       "      <th>perloan</th>\n",
       "      <th>savings</th>\n",
       "      <th>atm_user</th>\n",
       "      <th>markpl</th>\n",
       "      <th>age</th>\n",
       "      <th>cus_leng</th>\n",
       "      <th>response</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>2</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>32.666667</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>32.666667</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mortgage  life_ins  cre_card  deb_card  mob_bank  curr_acc  internet  \\\n",
       "0         0         0         0         0         0         0         0   \n",
       "1         1         1         0         1         1         0         0   \n",
       "2         1         1         0         1         0         0         0   \n",
       "3         1         1         1         1         0         1         0   \n",
       "4         1         1         0         1         0         0         0   \n",
       "5         0         0         0         1         1         1         0   \n",
       "6         0         0         0         1         0         0         0   \n",
       "7         1         1         0         1         0         0         0   \n",
       "8         1         1         0         1         0         0         0   \n",
       "\n",
       "   perloan  savings  atm_user  markpl        age  cus_leng  response  \n",
       "0        0        0         0       0  32.666667         1         0  \n",
       "1        0        0         1       0  18.000000         2         1  \n",
       "2        0        0         0       1  24.000000         2         1  \n",
       "3        0        0         1       1  36.000000         2         1  \n",
       "4        1        0         1       0  32.666667         2         0  \n",
       "5        0        0         0       0  18.000000         2         1  \n",
       "6        0        0         1       0  54.000000         1         1  \n",
       "7        0        0         1       0  46.000000         1         1  \n",
       "8        0        0         1       1  32.666667         3         0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Сравнение Python 2 и Python 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Беспроблемная работа с программным кодом"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from IPython.display import display\n",
    "plt.rc('font', family='Verdana')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Построение модели случайного леса и работа с полученными результатами"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Подготовка данных в pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer</th>\n",
       "      <th>State</th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>Effective To Date</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>Location Code</th>\n",
       "      <th>Marital Status</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
       "      <th>Months Since Last Claim</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
       "      <th>Number of Policies</th>\n",
       "      <th>Policy Type</th>\n",
       "      <th>Sales Channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BU79786</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2763.519279</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>24.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>56274</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QZ44356</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>6979.535903</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>31.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AI49188</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>12887.431650</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>19.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>48767</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WW63253</td>\n",
       "      <td>California</td>\n",
       "      <td>7645.861827</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>20.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>106.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HB64268</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2813.692575</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>02.03.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>43836</td>\n",
       "      <td>Rural</td>\n",
       "      <td>Single</td>\n",
       "      <td>73.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>OC83172</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>8256.297800</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>25.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>62902</td>\n",
       "      <td>Rural</td>\n",
       "      <td>Married</td>\n",
       "      <td>69.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Web</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>XZ87318</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>5380.898636</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>24.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>55350</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CF85061</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>7216.100311</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Master</td>\n",
       "      <td>18.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Single</td>\n",
       "      <td>101.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DY87989</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>24127.504020</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>26.01.2011</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>14072</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>71.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BQ94931</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>7388.178085</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>28812</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Married</td>\n",
       "      <td>93.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Special Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SX51350</td>\n",
       "      <td>California</td>\n",
       "      <td>4738.992022</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>21.02.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>67.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>VQ65197</td>\n",
       "      <td>California</td>\n",
       "      <td>8197.197078</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>01.06.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>110.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>DP39365</td>\n",
       "      <td>California</td>\n",
       "      <td>8798.797003</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Master</td>\n",
       "      <td>02.06.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>77026</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Married</td>\n",
       "      <td>110.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>SJ95423</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>8819.018934</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>01.10.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>99845</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>110.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>IL66569</td>\n",
       "      <td>California</td>\n",
       "      <td>5384.431665</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>18.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>83689</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Single</td>\n",
       "      <td>70.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>BW63560</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>7463.139377</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>17.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>24599</td>\n",
       "      <td>Rural</td>\n",
       "      <td>Married</td>\n",
       "      <td>64.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>FV94802</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>2566.867823</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>02.06.2011</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>25049</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>67.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>OE15005</td>\n",
       "      <td>California</td>\n",
       "      <td>3945.241604</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>01.05.2011</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>28855</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>101.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>WC83389</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>5710.333115</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>27.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>51148</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Married</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>FL50705</td>\n",
       "      <td>California</td>\n",
       "      <td>8162.617053</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>14.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>66140</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>101.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ZK25313</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>2872.051273</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>19.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>57749</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>SV62436</td>\n",
       "      <td>Washington</td>\n",
       "      <td>3041.791561</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>21.01.2011</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>13789</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>YH23384</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>24127.504020</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>26.01.2011</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>14072</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>71.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>TZ98966</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>2450.190996</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>24.02.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>73.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>HM55802</td>\n",
       "      <td>California</td>\n",
       "      <td>2392.107890</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>02.05.2011</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>17870</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>61.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>FS42516</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>5802.065978</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>29.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>97541</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>72.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>US89481</td>\n",
       "      <td>California</td>\n",
       "      <td>3946.372085</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>28.02.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>HO30839</td>\n",
       "      <td>Washington</td>\n",
       "      <td>5346.916576</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>02.12.2011</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>10511</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Married</td>\n",
       "      <td>139.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>GE62437</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>12902.560140</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>College</td>\n",
       "      <td>02.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>86584</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>111.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>EJ77678</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>3235.360468</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>02.07.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>75690</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8263</th>\n",
       "      <td>AS18084</td>\n",
       "      <td>California</td>\n",
       "      <td>11638.899470</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>26.01.2011</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>F</td>\n",
       "      <td>25370</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>102.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8264</th>\n",
       "      <td>FY21364</td>\n",
       "      <td>California</td>\n",
       "      <td>7376.795372</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>22.02.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>105.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8265</th>\n",
       "      <td>LL73047</td>\n",
       "      <td>California</td>\n",
       "      <td>7892.088107</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>26.01.2011</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>28672</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>71.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8266</th>\n",
       "      <td>CG15505</td>\n",
       "      <td>California</td>\n",
       "      <td>19160.989940</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>20.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>22705</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>239.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8267</th>\n",
       "      <td>ZZ22047</td>\n",
       "      <td>Washington</td>\n",
       "      <td>5548.031892</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>13.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>67798</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8268</th>\n",
       "      <td>NG56399</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>8319.529200</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>01.07.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>61367</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>70.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8269</th>\n",
       "      <td>MD45928</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>13770.976180</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Premium</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>02.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>59207</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>116.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8270</th>\n",
       "      <td>OV29928</td>\n",
       "      <td>Washington</td>\n",
       "      <td>5225.253777</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>24.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>67423</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Married</td>\n",
       "      <td>65.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8271</th>\n",
       "      <td>OR28030</td>\n",
       "      <td>California</td>\n",
       "      <td>16979.797570</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>17.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>35095</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>73.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8272</th>\n",
       "      <td>LO48748</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>7485.356469</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>30.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>26380</td>\n",
       "      <td>Rural</td>\n",
       "      <td>Single</td>\n",
       "      <td>96.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Web</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8273</th>\n",
       "      <td>FX95323</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>2639.644171</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>31.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>88731</td>\n",
       "      <td>Rural</td>\n",
       "      <td>Married</td>\n",
       "      <td>66.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8274</th>\n",
       "      <td>AG85127</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>8085.448545</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>14.01.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>61409</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Married</td>\n",
       "      <td>68.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Special Auto</td>\n",
       "      <td>Web</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8275</th>\n",
       "      <td>JN33628</td>\n",
       "      <td>California</td>\n",
       "      <td>12316.796980</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>22.02.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>167.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8276</th>\n",
       "      <td>QU69375</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>5568.947534</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Extended</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>01.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>79.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8277</th>\n",
       "      <td>FM37864</td>\n",
       "      <td>California</td>\n",
       "      <td>3571.828310</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>01.09.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>74931</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>89.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8278</th>\n",
       "      <td>IL23615</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>3350.244285</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>College</td>\n",
       "      <td>21.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>74770</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>86.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8279</th>\n",
       "      <td>FZ44411</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>2716.190293</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>30.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>95.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8280</th>\n",
       "      <td>JE32215</td>\n",
       "      <td>California</td>\n",
       "      <td>38887.903400</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>14.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>44299</td>\n",
       "      <td>Rural</td>\n",
       "      <td>Married</td>\n",
       "      <td>107.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8281</th>\n",
       "      <td>FQ88964</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>2272.447229</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>25.02.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>71.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8282</th>\n",
       "      <td>WW22291</td>\n",
       "      <td>California</td>\n",
       "      <td>2849.252467</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Master</td>\n",
       "      <td>16.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>63326</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>72.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8283</th>\n",
       "      <td>EV39637</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>5328.320299</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>02.12.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>73.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8284</th>\n",
       "      <td>TG36139</td>\n",
       "      <td>California</td>\n",
       "      <td>4679.977728</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>02.10.2011</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>21720</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>128.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8285</th>\n",
       "      <td>XN25550</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>5345.201117</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>College</td>\n",
       "      <td>01.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>55571</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>135.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8286</th>\n",
       "      <td>NG94966</td>\n",
       "      <td>California</td>\n",
       "      <td>2437.084486</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>27.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>34759</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>61.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8287</th>\n",
       "      <td>AD28349</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>4637.544647</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>23.02.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>68.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8288</th>\n",
       "      <td>VZ56705</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>8804.584902</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>25.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>38638</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>74.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8289</th>\n",
       "      <td>TQ82322</td>\n",
       "      <td>California</td>\n",
       "      <td>2438.689804</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>19.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>80927</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Single</td>\n",
       "      <td>62.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8290</th>\n",
       "      <td>CB77819</td>\n",
       "      <td>California</td>\n",
       "      <td>4736.347990</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>02.10.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>65.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Web</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8291</th>\n",
       "      <td>VG68427</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>5608.155723</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>17.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>81914</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Married</td>\n",
       "      <td>70.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8292</th>\n",
       "      <td>WO42164</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>6465.223746</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>02.07.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>92.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8293 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer       State  Customer Lifetime Value Response  Coverage  \\\n",
       "0     BU79786  Washington              2763.519279       No     Basic   \n",
       "1     QZ44356     Arizona              6979.535903       No  Extended   \n",
       "2     AI49188      Nevada             12887.431650       No   Premium   \n",
       "3     WW63253  California              7645.861827       No     Basic   \n",
       "4     HB64268  Washington              2813.692575       No     Basic   \n",
       "5     OC83172      Oregon              8256.297800      Yes     Basic   \n",
       "6     XZ87318      Oregon              5380.898636       No     Basic   \n",
       "7     CF85061     Arizona              7216.100311       No   Premium   \n",
       "8     DY87989      Oregon             24127.504020      Yes     Basic   \n",
       "9     BQ94931      Oregon              7388.178085       No  Extended   \n",
       "10    SX51350  California              4738.992022       No     Basic   \n",
       "11    VQ65197  California              8197.197078       No     Basic   \n",
       "12    DP39365  California              8798.797003       No   Premium   \n",
       "13    SJ95423     Arizona              8819.018934      Yes     Basic   \n",
       "14    IL66569  California              5384.431665       No     Basic   \n",
       "15    BW63560      Oregon              7463.139377       No     Basic   \n",
       "16    FV94802      Nevada              2566.867823       No     Basic   \n",
       "17    OE15005  California              3945.241604       No     Basic   \n",
       "18    WC83389      Oregon              5710.333115       No     Basic   \n",
       "19    FL50705  California              8162.617053       No   Premium   \n",
       "20    ZK25313      Oregon              2872.051273       No     Basic   \n",
       "21    SV62436  Washington              3041.791561       No  Extended   \n",
       "22    YH23384     Arizona             24127.504020      Yes     Basic   \n",
       "23    TZ98966      Nevada              2450.190996       No     Basic   \n",
       "24    HM55802  California              2392.107890       No     Basic   \n",
       "25    FS42516      Oregon              5802.065978       No     Basic   \n",
       "26    US89481  California              3946.372085       No   Premium   \n",
       "27    HO30839  Washington              5346.916576       No  Extended   \n",
       "28    GE62437     Arizona             12902.560140       No   Premium   \n",
       "29    EJ77678      Oregon              3235.360468       No  Extended   \n",
       "...       ...         ...                      ...      ...       ...   \n",
       "8263  AS18084  California             11638.899470      Yes     Basic   \n",
       "8264  FY21364  California              7376.795372       No     Basic   \n",
       "8265  LL73047  California              7892.088107       No     Basic   \n",
       "8266  CG15505  California             19160.989940      Yes  Extended   \n",
       "8267  ZZ22047  Washington              5548.031892      Yes     Basic   \n",
       "8268  NG56399     Arizona              8319.529200       No     Basic   \n",
       "8269  MD45928     Arizona             13770.976180      Yes   Premium   \n",
       "8270  OV29928  Washington              5225.253777       No     Basic   \n",
       "8271  OR28030  California             16979.797570      Yes     Basic   \n",
       "8272  LO48748      Oregon              7485.356469       No  Extended   \n",
       "8273  FX95323      Oregon              2639.644171       No     Basic   \n",
       "8274  AG85127      Oregon              8085.448545       No     Basic   \n",
       "8275  JN33628  California             12316.796980       No   Premium   \n",
       "8276  QU69375      Nevada              5568.947534      Yes  Extended   \n",
       "8277  FM37864  California              3571.828310       No  Extended   \n",
       "8278  IL23615      Oregon              3350.244285       No  Extended   \n",
       "8279  FZ44411     Arizona              2716.190293       No  Extended   \n",
       "8280  JE32215  California             38887.903400       No   Premium   \n",
       "8281  FQ88964     Arizona              2272.447229       No     Basic   \n",
       "8282  WW22291  California              2849.252467       No     Basic   \n",
       "8283  EV39637      Oregon              5328.320299       No     Basic   \n",
       "8284  TG36139  California              4679.977728       No  Extended   \n",
       "8285  XN25550      Oregon              5345.201117       No  Extended   \n",
       "8286  NG94966  California              2437.084486       No     Basic   \n",
       "8287  AD28349     Arizona              4637.544647       No     Basic   \n",
       "8288  VZ56705      Oregon              8804.584902       No     Basic   \n",
       "8289  TQ82322  California              2438.689804       No     Basic   \n",
       "8290  CB77819  California              4736.347990       No     Basic   \n",
       "8291  VG68427     Arizona              5608.155723       No     Basic   \n",
       "8292  WO42164      Oregon              6465.223746       No  Extended   \n",
       "\n",
       "                 Education Effective To Date EmploymentStatus Gender  Income  \\\n",
       "0                 Bachelor        24.02.2011         Employed      F   56274   \n",
       "1                 Bachelor        31.01.2011       Unemployed      F       0   \n",
       "2                 Bachelor        19.02.2011         Employed      F   48767   \n",
       "3                 Bachelor        20.01.2011       Unemployed      M       0   \n",
       "4                 Bachelor        02.03.2011         Employed      M   43836   \n",
       "5                 Bachelor        25.01.2011         Employed      F   62902   \n",
       "6                  College        24.02.2011         Employed      F   55350   \n",
       "7                   Master        18.01.2011       Unemployed      M       0   \n",
       "8                 Bachelor        26.01.2011    Medical Leave      M   14072   \n",
       "9                      NaN        17.02.2011         Employed      F   28812   \n",
       "10                 College        21.02.2011       Unemployed      M       0   \n",
       "11                 College        01.06.2011       Unemployed      F       0   \n",
       "12                  Master        02.06.2011         Employed      M   77026   \n",
       "13    High School or Below        01.10.2011         Employed      M   99845   \n",
       "14                 College        18.01.2011         Employed      M   83689   \n",
       "15                Bachelor        17.01.2011         Employed      F   24599   \n",
       "16    High School or Below        02.06.2011    Medical Leave      M   25049   \n",
       "17                 College        01.05.2011    Medical Leave      M   28855   \n",
       "18                 College        27.02.2011         Employed      M   51148   \n",
       "19    High School or Below        14.01.2011         Employed      F   66140   \n",
       "20    High School or Below        19.02.2011         Employed      M   57749   \n",
       "21                Bachelor        21.01.2011         Disabled      F   13789   \n",
       "22                Bachelor        26.01.2011    Medical Leave      M   14072   \n",
       "23                Bachelor        24.02.2011       Unemployed      F       0   \n",
       "24                Bachelor        02.05.2011         Disabled      F   17870   \n",
       "25                 College        29.01.2011         Employed      M   97541   \n",
       "26                Bachelor        28.02.2011       Unemployed      F       0   \n",
       "27                  Master        02.12.2011         Disabled      F   10511   \n",
       "28                 College        02.02.2011         Employed      F   86584   \n",
       "29                  Master        02.07.2011         Employed      F   75690   \n",
       "...                    ...               ...              ...    ...     ...   \n",
       "8263               College        26.01.2011    Medical Leave      F   25370   \n",
       "8264              Bachelor        22.02.2011       Unemployed      M       0   \n",
       "8265  High School or Below        26.01.2011         Disabled      F   28672   \n",
       "8266                Master        20.02.2011         Employed      F   22705   \n",
       "8267              Bachelor        13.01.2011         Employed      M   67798   \n",
       "8268  High School or Below        01.07.2011         Employed      M   61367   \n",
       "8269  High School or Below        02.01.2011         Employed      F   59207   \n",
       "8270               College        24.02.2011         Employed      F   67423   \n",
       "8271              Bachelor        17.01.2011         Employed      M   35095   \n",
       "8272                Master        30.01.2011         Employed      F   26380   \n",
       "8273               College        31.01.2011         Employed      M   88731   \n",
       "8274              Bachelor        14.01.2011         Employed      M   61409   \n",
       "8275              Bachelor        22.02.2011       Unemployed      M       0   \n",
       "8276  High School or Below        01.01.2011       Unemployed      M       0   \n",
       "8277              Bachelor        01.09.2011         Employed      F   74931   \n",
       "8278               College        21.02.2011         Employed      M   74770   \n",
       "8279              Bachelor        30.01.2011       Unemployed      M       0   \n",
       "8280              Bachelor        14.02.2011         Employed      F   44299   \n",
       "8281               College        25.02.2011       Unemployed      M       0   \n",
       "8282                Master        16.02.2011         Employed      M   63326   \n",
       "8283  High School or Below        02.12.2011       Unemployed      F       0   \n",
       "8284  High School or Below        02.10.2011         Disabled      F   21720   \n",
       "8285               College        01.02.2011         Employed      M   55571   \n",
       "8286               College        27.02.2011         Employed      M   34759   \n",
       "8287  High School or Below        23.02.2011       Unemployed      M       0   \n",
       "8288              Bachelor        25.02.2011         Employed      M   38638   \n",
       "8289              Bachelor        19.02.2011         Employed      F   80927   \n",
       "8290  High School or Below        02.10.2011       Unemployed      M       0   \n",
       "8291  High School or Below        17.02.2011         Employed      M   81914   \n",
       "8292  High School or Below        02.07.2011       Unemployed      M       0   \n",
       "\n",
       "     Location Code Marital Status  Monthly Premium Auto  \\\n",
       "0         Suburban        Married                   NaN   \n",
       "1         Suburban         Single                   NaN   \n",
       "2         Suburban        Married                 108.0   \n",
       "3         Suburban        Married                 106.0   \n",
       "4            Rural         Single                  73.0   \n",
       "5            Rural        Married                  69.0   \n",
       "6         Suburban        Married                  67.0   \n",
       "7            Urban         Single                 101.0   \n",
       "8         Suburban       Divorced                  71.0   \n",
       "9            Urban        Married                  93.0   \n",
       "10        Suburban         Single                  67.0   \n",
       "11        Suburban        Married                 110.0   \n",
       "12           Urban        Married                 110.0   \n",
       "13        Suburban        Married                 110.0   \n",
       "14           Urban         Single                  70.0   \n",
       "15           Rural        Married                  64.0   \n",
       "16        Suburban        Married                  67.0   \n",
       "17        Suburban        Married                 101.0   \n",
       "18           Urban        Married                   NaN   \n",
       "19        Suburban        Married                 101.0   \n",
       "20        Suburban         Single                   NaN   \n",
       "21        Suburban       Divorced                   NaN   \n",
       "22        Suburban       Divorced                  71.0   \n",
       "23        Suburban         Single                  73.0   \n",
       "24        Suburban        Married                  61.0   \n",
       "25        Suburban        Married                  72.0   \n",
       "26        Suburban         Single                   NaN   \n",
       "27           Urban        Married                 139.0   \n",
       "28        Suburban         Single                 111.0   \n",
       "29        Suburban        Married                  80.0   \n",
       "...            ...            ...                   ...   \n",
       "8263      Suburban        Married                 102.0   \n",
       "8264      Suburban         Single                 105.0   \n",
       "8265      Suburban       Divorced                  71.0   \n",
       "8266      Suburban       Divorced                 239.0   \n",
       "8267      Suburban       Divorced                  69.0   \n",
       "8268      Suburban       Divorced                  70.0   \n",
       "8269      Suburban         Single                 116.0   \n",
       "8270         Urban        Married                  65.0   \n",
       "8271      Suburban       Divorced                  73.0   \n",
       "8272         Rural         Single                  96.0   \n",
       "8273         Rural        Married                  66.0   \n",
       "8274         Urban        Married                  68.0   \n",
       "8275      Suburban        Married                 167.0   \n",
       "8276      Suburban         Single                  79.0   \n",
       "8277         Urban       Divorced                  89.0   \n",
       "8278      Suburban         Single                  86.0   \n",
       "8279      Suburban        Married                  95.0   \n",
       "8280         Rural        Married                 107.0   \n",
       "8281      Suburban         Single                  71.0   \n",
       "8282      Suburban       Divorced                  72.0   \n",
       "8283      Suburban         Single                  73.0   \n",
       "8284      Suburban         Single                 128.0   \n",
       "8285      Suburban        Married                 135.0   \n",
       "8286      Suburban       Divorced                  61.0   \n",
       "8287      Suburban       Divorced                  68.0   \n",
       "8288      Suburban        Married                  74.0   \n",
       "8289         Urban         Single                  62.0   \n",
       "8290      Suburban         Single                  65.0   \n",
       "8291         Urban        Married                  70.0   \n",
       "8292      Suburban         Single                  92.0   \n",
       "\n",
       "      Months Since Last Claim  Months Since Policy Inception  \\\n",
       "0                        32.0                            5.0   \n",
       "1                        13.0                           42.0   \n",
       "2                         NaN                           38.0   \n",
       "3                        18.0                           65.0   \n",
       "4                        12.0                           44.0   \n",
       "5                        14.0                           94.0   \n",
       "6                         0.0                           13.0   \n",
       "7                         0.0                           68.0   \n",
       "8                        13.0                            3.0   \n",
       "9                        17.0                            NaN   \n",
       "10                        NaN                            5.0   \n",
       "11                       27.0                           87.0   \n",
       "12                        9.0                            NaN   \n",
       "13                       23.0                           25.0   \n",
       "14                       21.0                            NaN   \n",
       "15                       12.0                           50.0   \n",
       "16                       14.0                            7.0   \n",
       "17                       12.0                           59.0   \n",
       "18                        9.0                            1.0   \n",
       "19                       11.0                           21.0   \n",
       "20                       31.0                           21.0   \n",
       "21                        8.0                           49.0   \n",
       "22                       13.0                            3.0   \n",
       "23                        4.0                           44.0   \n",
       "24                       30.0                           91.0   \n",
       "25                       22.0                            1.0   \n",
       "26                       15.0                           47.0   \n",
       "27                       33.0                            NaN   \n",
       "28                       33.0                           54.0   \n",
       "29                        NaN                           44.0   \n",
       "...                       ...                            ...   \n",
       "8263                     10.0                           77.0   \n",
       "8264                     31.0                           85.0   \n",
       "8265                     14.0                           34.0   \n",
       "8266                     19.0                           59.0   \n",
       "8267                      1.0                           78.0   \n",
       "8268                      7.0                           85.0   \n",
       "8269                     23.0                           21.0   \n",
       "8270                     24.0                            0.0   \n",
       "8271                     25.0                           56.0   \n",
       "8272                     29.0                           70.0   \n",
       "8273                     10.0                           72.0   \n",
       "8274                     30.0                           80.0   \n",
       "8275                     30.0                           40.0   \n",
       "8276                     21.0                           53.0   \n",
       "8277                     13.0                           16.0   \n",
       "8278                     23.0                           10.0   \n",
       "8279                     14.0                           81.0   \n",
       "8280                      0.0                           73.0   \n",
       "8281                     22.0                           10.0   \n",
       "8282                      2.0                           34.0   \n",
       "8283                     12.0                           42.0   \n",
       "8284                      5.0                            7.0   \n",
       "8285                      4.0                           46.0   \n",
       "8286                     30.0                           84.0   \n",
       "8287                     18.0                           81.0   \n",
       "8288                      5.0                           84.0   \n",
       "8289                     25.0                            8.0   \n",
       "8290                     33.0                            1.0   \n",
       "8291                      6.0                           33.0   \n",
       "8292                      9.0                           24.0   \n",
       "\n",
       "      Number of Open Complaints  Number of Policies     Policy Type  \\\n",
       "0                           NaN                 1.0  Corporate Auto   \n",
       "1                           NaN                 8.0   Personal Auto   \n",
       "2                           0.0                 2.0   Personal Auto   \n",
       "3                           0.0                 7.0  Corporate Auto   \n",
       "4                           0.0                 1.0   Personal Auto   \n",
       "5                           0.0                 2.0   Personal Auto   \n",
       "6                           0.0                 9.0  Corporate Auto   \n",
       "7                           0.0                 4.0  Corporate Auto   \n",
       "8                           0.0                 2.0  Corporate Auto   \n",
       "9                           0.0                 8.0    Special Auto   \n",
       "10                          0.0                 3.0   Personal Auto   \n",
       "11                          0.0                 3.0   Personal Auto   \n",
       "12                          2.0                 3.0  Corporate Auto   \n",
       "13                          1.0                 NaN  Corporate Auto   \n",
       "14                          2.0                 8.0  Corporate Auto   \n",
       "15                          1.0                 NaN  Corporate Auto   \n",
       "16                          0.0                 1.0   Personal Auto   \n",
       "17                          0.0                 1.0   Personal Auto   \n",
       "18                          NaN                 7.0   Personal Auto   \n",
       "19                          0.0                 3.0  Corporate Auto   \n",
       "20                          0.0                 1.0   Personal Auto   \n",
       "21                          0.0                 1.0   Personal Auto   \n",
       "22                          0.0                 2.0   Personal Auto   \n",
       "23                          3.0                 1.0  Corporate Auto   \n",
       "24                          0.0                 1.0  Corporate Auto   \n",
       "25                          0.0                 3.0   Personal Auto   \n",
       "26                          0.0                 1.0   Personal Auto   \n",
       "27                          0.0                 1.0  Corporate Auto   \n",
       "28                          2.0                 NaN   Personal Auto   \n",
       "29                          1.0                 1.0   Personal Auto   \n",
       "...                         ...                 ...             ...   \n",
       "8263                        0.0                 2.0   Personal Auto   \n",
       "8264                        0.0                 5.0  Corporate Auto   \n",
       "8265                        0.0                 2.0   Personal Auto   \n",
       "8266                        0.0                 7.0   Personal Auto   \n",
       "8267                        0.0                 9.0  Corporate Auto   \n",
       "8268                        0.0                 2.0   Personal Auto   \n",
       "8269                        0.0                 2.0   Personal Auto   \n",
       "8270                        0.0                 9.0  Corporate Auto   \n",
       "8271                        0.0                 2.0  Corporate Auto   \n",
       "8272                        0.0                 4.0   Personal Auto   \n",
       "8273                        0.0                 1.0   Personal Auto   \n",
       "8274                        0.0                 2.0    Special Auto   \n",
       "8275                        0.0                 5.0   Personal Auto   \n",
       "8276                        1.0                 7.0  Corporate Auto   \n",
       "8277                        0.0                 1.0   Personal Auto   \n",
       "8278                        0.0                 1.0   Personal Auto   \n",
       "8279                        5.0                 1.0  Corporate Auto   \n",
       "8280                        0.0                 2.0   Personal Auto   \n",
       "8281                        1.0                 1.0   Personal Auto   \n",
       "8282                        0.0                 1.0   Personal Auto   \n",
       "8283                        0.0                 7.0   Personal Auto   \n",
       "8284                        0.0                 1.0  Corporate Auto   \n",
       "8285                        0.0                 1.0   Personal Auto   \n",
       "8286                        0.0                 1.0   Personal Auto   \n",
       "8287                        0.0                 3.0   Personal Auto   \n",
       "8288                        0.0                 2.0   Personal Auto   \n",
       "8289                        0.0                 1.0   Personal Auto   \n",
       "8290                        0.0                 3.0   Personal Auto   \n",
       "8291                        0.0                 6.0  Corporate Auto   \n",
       "8292                        0.0                 3.0   Personal Auto   \n",
       "\n",
       "     Sales Channel  \n",
       "0            Agent  \n",
       "1            Agent  \n",
       "2            Agent  \n",
       "3      Call Center  \n",
       "4            Agent  \n",
       "5              Web  \n",
       "6            Agent  \n",
       "7            Agent  \n",
       "8            Agent  \n",
       "9           Branch  \n",
       "10           Agent  \n",
       "11           Agent  \n",
       "12           Agent  \n",
       "13          Branch  \n",
       "14     Call Center  \n",
       "15          Branch  \n",
       "16     Call Center  \n",
       "17     Call Center  \n",
       "18          Branch  \n",
       "19     Call Center  \n",
       "20          Branch  \n",
       "21     Call Center  \n",
       "22           Agent  \n",
       "23          Branch  \n",
       "24          Branch  \n",
       "25     Call Center  \n",
       "26           Agent  \n",
       "27          Branch  \n",
       "28     Call Center  \n",
       "29          Branch  \n",
       "...            ...  \n",
       "8263        Branch  \n",
       "8264         Agent  \n",
       "8265        Branch  \n",
       "8266         Agent  \n",
       "8267         Agent  \n",
       "8268        Branch  \n",
       "8269         Agent  \n",
       "8270         Agent  \n",
       "8271   Call Center  \n",
       "8272           Web  \n",
       "8273         Agent  \n",
       "8274           Web  \n",
       "8275        Branch  \n",
       "8276         Agent  \n",
       "8277         Agent  \n",
       "8278        Branch  \n",
       "8279   Call Center  \n",
       "8280        Branch  \n",
       "8281   Call Center  \n",
       "8282   Call Center  \n",
       "8283        Branch  \n",
       "8284        Branch  \n",
       "8285         Agent  \n",
       "8286         Agent  \n",
       "8287   Call Center  \n",
       "8288         Agent  \n",
       "8289        Branch  \n",
       "8290           Web  \n",
       "8291        Branch  \n",
       "8292   Call Center  \n",
       "\n",
       "[8293 rows x 19 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = pd.read_csv(\"C:/Trees/Insurance.csv\", encoding='latin-1')\n",
    "display(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8293, 19)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        text-align: right;\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer</th>\n",
       "      <th>State</th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>Effective To Date</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>Location Code</th>\n",
       "      <th>Marital Status</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
       "      <th>Months Since Last Claim</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
       "      <th>Number of Policies</th>\n",
       "      <th>Policy Type</th>\n",
       "      <th>Sales Channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BU79786</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2763.519279</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>24.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>56274</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QZ44356</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>6979.535903</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>31.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AI49188</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>12887.431650</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>19.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>48767</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WW63253</td>\n",
       "      <td>California</td>\n",
       "      <td>7645.861827</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>20.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>106.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HB64268</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2813.692575</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>02.03.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>43836</td>\n",
       "      <td>Rural</td>\n",
       "      <td>Single</td>\n",
       "      <td>73.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Customer       State  Customer Lifetime Value Response  Coverage Education  \\\n",
       "0  BU79786  Washington              2763.519279       No     Basic  Bachelor   \n",
       "1  QZ44356     Arizona              6979.535903       No  Extended  Bachelor   \n",
       "2  AI49188      Nevada             12887.431650       No   Premium  Bachelor   \n",
       "3  WW63253  California              7645.861827       No     Basic  Bachelor   \n",
       "4  HB64268  Washington              2813.692575       No     Basic  Bachelor   \n",
       "\n",
       "  Effective To Date EmploymentStatus Gender  Income Location Code  \\\n",
       "0        24.02.2011         Employed      F   56274      Suburban   \n",
       "1        31.01.2011       Unemployed      F       0      Suburban   \n",
       "2        19.02.2011         Employed      F   48767      Suburban   \n",
       "3        20.01.2011       Unemployed      M       0      Suburban   \n",
       "4        02.03.2011         Employed      M   43836         Rural   \n",
       "\n",
       "  Marital Status  Monthly Premium Auto  Months Since Last Claim  \\\n",
       "0        Married                   NaN                     32.0   \n",
       "1         Single                   NaN                     13.0   \n",
       "2        Married                 108.0                      NaN   \n",
       "3        Married                 106.0                     18.0   \n",
       "4         Single                  73.0                     12.0   \n",
       "\n",
       "   Months Since Policy Inception  Number of Open Complaints  \\\n",
       "0                            5.0                        NaN   \n",
       "1                           42.0                        NaN   \n",
       "2                           38.0                        0.0   \n",
       "3                           65.0                        0.0   \n",
       "4                           44.0                        0.0   \n",
       "\n",
       "   Number of Policies     Policy Type Sales Channel  \n",
       "0                 1.0  Corporate Auto         Agent  \n",
       "1                 8.0   Personal Auto         Agent  \n",
       "2                 2.0   Personal Auto         Agent  \n",
       "3                 7.0  Corporate Auto   Call Center  \n",
       "4                 1.0   Personal Auto         Agent  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer</th>\n",
       "      <th>State</th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>Effective To Date</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>Location Code</th>\n",
       "      <th>Marital Status</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
       "      <th>Months Since Last Claim</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
       "      <th>Number of Policies</th>\n",
       "      <th>Policy Type</th>\n",
       "      <th>Sales Channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8288</th>\n",
       "      <td>VZ56705</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>8804.584902</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>25.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>38638</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>74.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8289</th>\n",
       "      <td>TQ82322</td>\n",
       "      <td>California</td>\n",
       "      <td>2438.689804</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>19.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>80927</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Single</td>\n",
       "      <td>62.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8290</th>\n",
       "      <td>CB77819</td>\n",
       "      <td>California</td>\n",
       "      <td>4736.347990</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>02.10.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>65.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Web</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8291</th>\n",
       "      <td>VG68427</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>5608.155723</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>17.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>81914</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Married</td>\n",
       "      <td>70.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8292</th>\n",
       "      <td>WO42164</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>6465.223746</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>02.07.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Single</td>\n",
       "      <td>92.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Customer       State  Customer Lifetime Value Response  Coverage  \\\n",
       "8288  VZ56705      Oregon              8804.584902       No     Basic   \n",
       "8289  TQ82322  California              2438.689804       No     Basic   \n",
       "8290  CB77819  California              4736.347990       No     Basic   \n",
       "8291  VG68427     Arizona              5608.155723       No     Basic   \n",
       "8292  WO42164      Oregon              6465.223746       No  Extended   \n",
       "\n",
       "                 Education Effective To Date EmploymentStatus Gender  Income  \\\n",
       "8288              Bachelor        25.02.2011         Employed      M   38638   \n",
       "8289              Bachelor        19.02.2011         Employed      F   80927   \n",
       "8290  High School or Below        02.10.2011       Unemployed      M       0   \n",
       "8291  High School or Below        17.02.2011         Employed      M   81914   \n",
       "8292  High School or Below        02.07.2011       Unemployed      M       0   \n",
       "\n",
       "     Location Code Marital Status  Monthly Premium Auto  \\\n",
       "8288      Suburban        Married                  74.0   \n",
       "8289         Urban         Single                  62.0   \n",
       "8290      Suburban         Single                  65.0   \n",
       "8291         Urban        Married                  70.0   \n",
       "8292      Suburban         Single                  92.0   \n",
       "\n",
       "      Months Since Last Claim  Months Since Policy Inception  \\\n",
       "8288                      5.0                           84.0   \n",
       "8289                     25.0                            8.0   \n",
       "8290                     33.0                            1.0   \n",
       "8291                      6.0                           33.0   \n",
       "8292                      9.0                           24.0   \n",
       "\n",
       "      Number of Open Complaints  Number of Policies     Policy Type  \\\n",
       "8288                        0.0                 2.0   Personal Auto   \n",
       "8289                        0.0                 1.0   Personal Auto   \n",
       "8290                        0.0                 3.0   Personal Auto   \n",
       "8291                        0.0                 6.0  Corporate Auto   \n",
       "8292                        0.0                 3.0   Personal Auto   \n",
       "\n",
       "     Sales Channel  \n",
       "8288         Agent  \n",
       "8289        Branch  \n",
       "8290           Web  \n",
       "8291        Branch  \n",
       "8292   Call Center  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer</th>\n",
       "      <th>State</th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>Effective To Date</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>Location Code</th>\n",
       "      <th>Marital Status</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
       "      <th>Months Since Last Claim</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
       "      <th>Number of Policies</th>\n",
       "      <th>Policy Type</th>\n",
       "      <th>Sales Channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BU79786</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2763.519279</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>24.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>56274</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Customer       State  Customer Lifetime Value Response Coverage Education  \\\n",
       "0  BU79786  Washington              2763.519279       No    Basic  Bachelor   \n",
       "\n",
       "  Effective To Date EmploymentStatus Gender  Income Location Code  \\\n",
       "0        24.02.2011         Employed      F   56274      Suburban   \n",
       "\n",
       "  Marital Status  Monthly Premium Auto  Months Since Last Claim  \\\n",
       "0        Married                   NaN                     32.0   \n",
       "\n",
       "   Months Since Policy Inception  Number of Open Complaints  \\\n",
       "0                            5.0                        NaN   \n",
       "\n",
       "   Number of Policies     Policy Type Sales Channel  \n",
       "0                 1.0  Corporate Auto         Agent  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[:1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Income</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
       "      <th>Months Since Last Claim</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
       "      <th>Number of Policies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>8293.000000</td>\n",
       "      <td>8293.000000</td>\n",
       "      <td>8287.000000</td>\n",
       "      <td>8290.000000</td>\n",
       "      <td>8288.000000</td>\n",
       "      <td>8290.000000</td>\n",
       "      <td>8290.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7988.177822</td>\n",
       "      <td>37787.118654</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>48.145150</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>2.965259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6840.106687</td>\n",
       "      <td>30393.997287</td>\n",
       "      <td>34.507260</td>\n",
       "      <td>10.093995</td>\n",
       "      <td>27.827279</td>\n",
       "      <td>0.915379</td>\n",
       "      <td>2.390010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1898.007675</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3982.266087</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5789.850900</td>\n",
       "      <td>34220.000000</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8960.280213</td>\n",
       "      <td>62452.000000</td>\n",
       "      <td>109.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>83325.381190</td>\n",
       "      <td>99981.000000</td>\n",
       "      <td>298.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Customer Lifetime Value        Income  Monthly Premium Auto  \\\n",
       "count              8293.000000   8293.000000           8287.000000   \n",
       "mean               7988.177822  37787.118654             93.196573   \n",
       "std                6840.106687  30393.997287             34.507260   \n",
       "min                1898.007675      0.000000             61.000000   \n",
       "25%                3982.266087      0.000000             68.000000   \n",
       "50%                5789.850900  34220.000000             83.000000   \n",
       "75%                8960.280213  62452.000000            109.000000   \n",
       "max               83325.381190  99981.000000            298.000000   \n",
       "\n",
       "       Months Since Last Claim  Months Since Policy Inception  \\\n",
       "count              8290.000000                    8288.000000   \n",
       "mean                 15.077925                      48.145150   \n",
       "std                  10.093995                      27.827279   \n",
       "min                   0.000000                       0.000000   \n",
       "25%                   6.000000                      24.000000   \n",
       "50%                  14.000000                      48.000000   \n",
       "75%                  23.000000                      71.000000   \n",
       "max                  35.000000                      99.000000   \n",
       "\n",
       "       Number of Open Complaints  Number of Policies  \n",
       "count                8290.000000         8290.000000  \n",
       "mean                    0.389626            2.965259  \n",
       "std                     0.915379            2.390010  \n",
       "min                     0.000000            1.000000  \n",
       "25%                     0.000000            1.000000  \n",
       "50%                     0.000000            2.000000  \n",
       "75%                     0.000000            4.000000  \n",
       "max                     5.000000            9.000000  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Customer                         8293\n",
       "State                            8293\n",
       "Customer Lifetime Value          8293\n",
       "Response                         8293\n",
       "Coverage                         8293\n",
       "Education                        8292\n",
       "Effective To Date                8293\n",
       "EmploymentStatus                 8293\n",
       "Gender                           8293\n",
       "Income                           8293\n",
       "Location Code                    8293\n",
       "Marital Status                   8293\n",
       "Monthly Premium Auto             8287\n",
       "Months Since Last Claim          8290\n",
       "Months Since Policy Inception    8288\n",
       "Number of Open Complaints        8290\n",
       "Number of Policies               8290\n",
       "Policy Type                      8293\n",
       "Sales Channel                    8293\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.count(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 8293 entries, 0 to 8292\n",
      "Data columns (total 19 columns):\n",
      "Customer                         8293 non-null object\n",
      "State                            8293 non-null object\n",
      "Customer Lifetime Value          8293 non-null float64\n",
      "Response                         8293 non-null object\n",
      "Coverage                         8293 non-null object\n",
      "Education                        8292 non-null object\n",
      "Effective To Date                8293 non-null object\n",
      "EmploymentStatus                 8293 non-null object\n",
      "Gender                           8293 non-null object\n",
      "Income                           8293 non-null int64\n",
      "Location Code                    8293 non-null object\n",
      "Marital Status                   8293 non-null object\n",
      "Monthly Premium Auto             8287 non-null float64\n",
      "Months Since Last Claim          8290 non-null float64\n",
      "Months Since Policy Inception    8288 non-null float64\n",
      "Number of Open Complaints        8290 non-null float64\n",
      "Number of Policies               8290 non-null float64\n",
      "Policy Type                      8293 non-null object\n",
      "Sales Channel                    8293 non-null object\n",
      "dtypes: float64(6), int64(1), object(12)\n",
      "memory usage: 1.2+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(data.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Customer                         8293\n",
       "State                            8293\n",
       "Customer Lifetime Value          8293\n",
       "Response                         8293\n",
       "Coverage                         8293\n",
       "Education                        8293\n",
       "Effective To Date                8293\n",
       "EmploymentStatus                 8293\n",
       "Gender                           8293\n",
       "Income                           8293\n",
       "Location Code                    8293\n",
       "Marital Status                   8293\n",
       "Monthly Premium Auto             8293\n",
       "Months Since Last Claim          8293\n",
       "Months Since Policy Inception    8293\n",
       "Number of Open Complaints        8293\n",
       "Number of Policies               8293\n",
       "Policy Type                      8293\n",
       "Sales Channel                    8293\n",
       "dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Monthly Premium Auto'].fillna(data['Monthly Premium Auto'].mean(), \n",
    "                                    inplace=True)\n",
    "data['Months Since Last Claim'].fillna(data['Months Since Last Claim'].mean(), \n",
    "                                       inplace=True)\n",
    "data['Months Since Policy Inception'].fillna(data['Months Since Policy Inception'].mean(),\n",
    "                                             inplace=True)\n",
    "data['Number of Open Complaints'].fillna(data['Number of Open Complaints'].mean(), \n",
    "                                         inplace=True)\n",
    "data['Number of Policies'].fillna(data['Number of Policies'].mean(), inplace=True)\n",
    "data['Education'].fillna(data['Education'].value_counts().index[0], inplace=True)\n",
    "data.count(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Customer', 'State', 'Response', 'Coverage', 'Education', 'Effective To Date', 'EmploymentStatus', 'Gender', 'Location Code', 'Marital Status', 'Policy Type', 'Sales Channel']\n",
      "['Customer Lifetime Value', 'Income', 'Monthly Premium Auto', 'Months Since Last Claim', 'Months Since Policy Inception', 'Number of Open Complaints', 'Number of Policies']\n"
     ]
    }
   ],
   "source": [
    "categorical_columns = [c for c in data.columns if data[c].dtype.name == 'object']\n",
    "numerical_columns   = [c for c in data.columns if data[c].dtype.name != 'object']\n",
    "print(categorical_columns)\n",
    "print(numerical_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer</th>\n",
       "      <th>State</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>Effective To Date</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Location Code</th>\n",
       "      <th>Marital Status</th>\n",
       "      <th>Policy Type</th>\n",
       "      <th>Sales Channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "      <td>8293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>8293</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>59</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>KR48903</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>01.10.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>Suburban</td>\n",
       "      <td>Married</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1</td>\n",
       "      <td>2535</td>\n",
       "      <td>7462</td>\n",
       "      <td>5041</td>\n",
       "      <td>2499</td>\n",
       "      <td>178</td>\n",
       "      <td>5191</td>\n",
       "      <td>4252</td>\n",
       "      <td>5225</td>\n",
       "      <td>4818</td>\n",
       "      <td>6203</td>\n",
       "      <td>3161</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Customer   State Response Coverage Education Effective To Date  \\\n",
       "count      8293    8293     8293     8293      8293              8293   \n",
       "unique     8293       5        2        3         5                59   \n",
       "top     KR48903  Oregon       No    Basic  Bachelor        01.10.2011   \n",
       "freq          1    2535     7462     5041      2499               178   \n",
       "\n",
       "       EmploymentStatus Gender Location Code Marital Status    Policy Type  \\\n",
       "count              8293   8293          8293           8293           8293   \n",
       "unique                5      2             3              3              3   \n",
       "top            Employed      F      Suburban        Married  Personal Auto   \n",
       "freq               5191   4252          5225           4818           6203   \n",
       "\n",
       "       Sales Channel  \n",
       "count           8293  \n",
       "unique             4  \n",
       "top            Agent  \n",
       "freq            3161  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[categorical_columns].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['BU79786' 'QZ44356' 'AI49188' ..., 'CB77819' 'VG68427' 'WO42164']\n",
      "['Washington' 'Arizona' 'Nevada' 'California' 'Oregon']\n",
      "['No' 'Yes']\n",
      "['Basic' 'Extended' 'Premium']\n",
      "['Bachelor' 'College' 'Master' 'High School or Below' 'Doctor']\n",
      "['24.02.2011' '31.01.2011' '19.02.2011' '20.01.2011' '02.03.2011'\n",
      " '25.01.2011' '18.01.2011' '26.01.2011' '17.02.2011' '21.02.2011'\n",
      " '01.06.2011' '02.06.2011' '01.10.2011' '17.01.2011' '01.05.2011'\n",
      " '27.02.2011' '14.01.2011' '21.01.2011' '02.05.2011' '29.01.2011'\n",
      " '28.02.2011' '02.12.2011' '02.02.2011' '02.07.2011' '22.01.2011'\n",
      " '13.02.2011' '15.01.2011' '01.08.2011' '01.11.2011' '28.01.2011'\n",
      " '02.08.2011' '23.02.2011' '01.02.2011' '16.02.2011' '27.01.2011'\n",
      " '23.01.2011' '01.09.2011' '02.11.2011' '02.04.2011' '02.01.2011'\n",
      " '15.02.2011' '26.02.2011' '16.01.2011' '01.01.2011' '02.10.2011'\n",
      " '24.01.2011' '25.02.2011' '01.12.2011' '02.09.2011' '19.01.2011'\n",
      " '01.04.2011' '14.02.2011' '20.02.2011' '18.02.2011' '01.03.2011'\n",
      " '13.01.2011' '30.01.2011' '22.02.2011' '01.07.2011']\n",
      "['Employed' 'Unemployed' 'Medical Leave' 'Disabled' 'Retired']\n",
      "['F' 'M']\n",
      "['Suburban' 'Rural' 'Urban']\n",
      "['Married' 'Single' 'Divorced']\n",
      "['Corporate Auto' 'Personal Auto' 'Special Auto']\n",
      "['Agent' 'Call Center' 'Web' 'Branch']\n"
     ]
    }
   ],
   "source": [
    "for c in categorical_columns:\n",
    "    print(data[c].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     7462\n",
       "Yes     831\n",
       "Name: Response, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"Response\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Policy Type</th>\n",
       "      <th>Corporate Auto</th>\n",
       "      <th>Personal Auto</th>\n",
       "      <th>Special Auto</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Response</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>1534</td>\n",
       "      <td>5599</td>\n",
       "      <td>329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>186</td>\n",
       "      <td>604</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Policy Type  Corporate Auto  Personal Auto  Special Auto\n",
       "Response                                                \n",
       "No                     1534           5599           329\n",
       "Yes                     186            604            41"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(data['Response'], data['Policy Type'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Policy Type</th>\n",
       "      <th>Corporate Auto</th>\n",
       "      <th>Personal Auto</th>\n",
       "      <th>Special Auto</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Response</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>1534</td>\n",
       "      <td>5599</td>\n",
       "      <td>329</td>\n",
       "      <td>7462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>186</td>\n",
       "      <td>604</td>\n",
       "      <td>41</td>\n",
       "      <td>831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>1720</td>\n",
       "      <td>6203</td>\n",
       "      <td>370</td>\n",
       "      <td>8293</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Policy Type  Corporate Auto  Personal Auto  Special Auto   All\n",
       "Response                                                      \n",
       "No                     1534           5599           329  7462\n",
       "Yes                     186            604            41   831\n",
       "All                    1720           6203           370  8293"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(data['Response'], data['Policy Type'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer</th>\n",
       "      <th>State</th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>Effective To Date</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>Location Code</th>\n",
       "      <th>Marital Status</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
       "      <th>Months Since Last Claim</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
       "      <th>Number of Policies</th>\n",
       "      <th>Policy Type</th>\n",
       "      <th>Sales Channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BU79786</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2763.519279</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>24.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>56274</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Married</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QZ44356</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>6979.535903</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>31.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Single</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AI49188</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>12887.431650</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>19.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>48767</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Married</td>\n",
       "      <td>108.000000</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WW63253</td>\n",
       "      <td>California</td>\n",
       "      <td>7645.861827</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>20.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Married</td>\n",
       "      <td>106.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HB64268</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2813.692575</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>02.03.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>43836</td>\n",
       "      <td>Rur</td>\n",
       "      <td>Single</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Customer       State  Customer Lifetime Value Response  Coverage Education  \\\n",
       "0  BU79786  Washington              2763.519279       No     Basic  Bachelor   \n",
       "1  QZ44356     Arizona              6979.535903       No  Extended  Bachelor   \n",
       "2  AI49188      Nevada             12887.431650       No   Premium  Bachelor   \n",
       "3  WW63253  California              7645.861827       No     Basic  Bachelor   \n",
       "4  HB64268  Washington              2813.692575       No     Basic  Bachelor   \n",
       "\n",
       "  Effective To Date EmploymentStatus Gender  Income Location Code  \\\n",
       "0        24.02.2011         Employed      F   56274           Sub   \n",
       "1        31.01.2011       Unemployed      F       0           Sub   \n",
       "2        19.02.2011         Employed      F   48767           Sub   \n",
       "3        20.01.2011       Unemployed      M       0           Sub   \n",
       "4        02.03.2011         Employed      M   43836           Rur   \n",
       "\n",
       "  Marital Status  Monthly Premium Auto  Months Since Last Claim  \\\n",
       "0        Married             93.196573                32.000000   \n",
       "1         Single             93.196573                13.000000   \n",
       "2        Married            108.000000                15.077925   \n",
       "3        Married            106.000000                18.000000   \n",
       "4         Single             73.000000                12.000000   \n",
       "\n",
       "   Months Since Policy Inception  Number of Open Complaints  \\\n",
       "0                            5.0                   0.389626   \n",
       "1                           42.0                   0.389626   \n",
       "2                           38.0                   0.000000   \n",
       "3                           65.0                   0.000000   \n",
       "4                           44.0                   0.000000   \n",
       "\n",
       "   Number of Policies     Policy Type Sales Channel  \n",
       "0                 1.0  Corporate Auto         Agent  \n",
       "1                 8.0   Personal Auto         Agent  \n",
       "2                 2.0   Personal Auto         Agent  \n",
       "3                 7.0  Corporate Auto   Call Center  \n",
       "4                 1.0   Personal Auto         Agent  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = {'Suburban':'Sub', 'Rural':'Rur', 'Urban':'Urb'}\n",
    "data['Location Code'] = data['Location Code'].map(d)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer</th>\n",
       "      <th>State</th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>Effective To Date</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>Location Code</th>\n",
       "      <th>Marital Status</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
       "      <th>Months Since Last Claim</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
       "      <th>Number of Policies</th>\n",
       "      <th>Policy Type</th>\n",
       "      <th>Sales Channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BU79786</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2763.519279</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>24.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>56274</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QZ44356</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>6979.535903</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>31.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AI49188</td>\n",
       "      <td>Nevada</td>\n",
       "      <td>12887.431650</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>19.02.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>48767</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>108.000000</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WW63253</td>\n",
       "      <td>California</td>\n",
       "      <td>7645.861827</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>20.01.2011</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>106.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>65.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HB64268</td>\n",
       "      <td>Washington</td>\n",
       "      <td>2813.692575</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>02.03.2011</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>43836</td>\n",
       "      <td>Rur</td>\n",
       "      <td>Sin</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Customer       State  Customer Lifetime Value Response  Coverage Education  \\\n",
       "0  BU79786  Washington              2763.519279       No     Basic  Bachelor   \n",
       "1  QZ44356     Arizona              6979.535903       No  Extended  Bachelor   \n",
       "2  AI49188      Nevada             12887.431650       No   Premium  Bachelor   \n",
       "3  WW63253  California              7645.861827       No     Basic  Bachelor   \n",
       "4  HB64268  Washington              2813.692575       No     Basic  Bachelor   \n",
       "\n",
       "  Effective To Date EmploymentStatus Gender  Income Location Code  \\\n",
       "0        24.02.2011         Employed      F   56274           Sub   \n",
       "1        31.01.2011       Unemployed      F       0           Sub   \n",
       "2        19.02.2011         Employed      F   48767           Sub   \n",
       "3        20.01.2011       Unemployed      M       0           Sub   \n",
       "4        02.03.2011         Employed      M   43836           Rur   \n",
       "\n",
       "  Marital Status  Monthly Premium Auto  Months Since Last Claim  \\\n",
       "0            Mar             93.196573                32.000000   \n",
       "1            Sin             93.196573                13.000000   \n",
       "2            Mar            108.000000                15.077925   \n",
       "3            Mar            106.000000                18.000000   \n",
       "4            Sin             73.000000                12.000000   \n",
       "\n",
       "   Months Since Policy Inception  Number of Open Complaints  \\\n",
       "0                            5.0                   0.389626   \n",
       "1                           42.0                   0.389626   \n",
       "2                           38.0                   0.000000   \n",
       "3                           65.0                   0.000000   \n",
       "4                           44.0                   0.000000   \n",
       "\n",
       "   Number of Policies     Policy Type Sales Channel  \n",
       "0                 1.0  Corporate Auto         Agent  \n",
       "1                 8.0   Personal Auto         Agent  \n",
       "2                 2.0   Personal Auto         Agent  \n",
       "3                 7.0  Corporate Auto   Call Center  \n",
       "4                 1.0   Personal Auto         Agent  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = {'Married':'Mar', 'Single':'Sin', 'Divorced':'Div'}\n",
    "data = data.replace({'Marital Status': f})\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Response</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>Education</th>\n",
       "      <th>EmploymentStatus</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>Location Code</th>\n",
       "      <th>Marital Status</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
       "      <th>Months Since Last Claim</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
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       "      <th>Sales Channel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Washington</td>\n",
       "      <td>2763.519279</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
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       "      <td>5.00000</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>6979.535903</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>42.00000</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Nevada</td>\n",
       "      <td>12887.431650</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>48767</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>108.000000</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>38.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>California</td>\n",
       "      <td>7645.861827</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>106.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>65.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Washington</td>\n",
       "      <td>2813.692575</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>43836</td>\n",
       "      <td>Rur</td>\n",
       "      <td>Sin</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>44.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>8256.297800</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>62902</td>\n",
       "      <td>Rur</td>\n",
       "      <td>Mar</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>94.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Web</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>5380.898636</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>55350</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>13.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>7216.100311</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Master</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Sin</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>68.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>24127.504020</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>14072</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>7388.178085</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>28812</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Mar</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>Special Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>California</td>\n",
       "      <td>4738.992022</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>5.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>California</td>\n",
       "      <td>8197.197078</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>87.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>California</td>\n",
       "      <td>8798.797003</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Master</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>77026</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Mar</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>8819.018934</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>99845</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>25.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.965259</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>California</td>\n",
       "      <td>5384.431665</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>83689</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Sin</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>7463.139377</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>24599</td>\n",
       "      <td>Rur</td>\n",
       "      <td>Mar</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>50.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.965259</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Nevada</td>\n",
       "      <td>2566.867823</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>25049</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>7.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>California</td>\n",
       "      <td>3945.241604</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>28855</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>59.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>5710.333115</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>51148</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Mar</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>California</td>\n",
       "      <td>8162.617053</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>66140</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>2872.051273</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>57749</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Washington</td>\n",
       "      <td>3041.791561</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>13789</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>49.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>24127.504020</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>M</td>\n",
       "      <td>14072</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Nevada</td>\n",
       "      <td>2450.190996</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>44.00000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>California</td>\n",
       "      <td>2392.107890</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>17870</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>91.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>5802.065978</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>97541</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>California</td>\n",
       "      <td>3946.372085</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>47.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Washington</td>\n",
       "      <td>5346.916576</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>10511</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Mar</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>12902.560140</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>86584</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>54.00000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.965259</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>3235.360468</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>75690</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>44.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8263</th>\n",
       "      <td>California</td>\n",
       "      <td>11638.899470</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Medical Leave</td>\n",
       "      <td>F</td>\n",
       "      <td>25370</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>102.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>77.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8264</th>\n",
       "      <td>California</td>\n",
       "      <td>7376.795372</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>85.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8265</th>\n",
       "      <td>California</td>\n",
       "      <td>7892.088107</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>28672</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>34.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8266</th>\n",
       "      <td>California</td>\n",
       "      <td>19160.989940</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>22705</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>239.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>59.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8267</th>\n",
       "      <td>Washington</td>\n",
       "      <td>5548.031892</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>67798</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>78.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8268</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>8319.529200</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>61367</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>85.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8269</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>13770.976180</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Premium</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>59207</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>116.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8270</th>\n",
       "      <td>Washington</td>\n",
       "      <td>5225.253777</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>67423</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Mar</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8271</th>\n",
       "      <td>California</td>\n",
       "      <td>16979.797570</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>35095</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>56.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8272</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>7485.356469</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Master</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>26380</td>\n",
       "      <td>Rur</td>\n",
       "      <td>Sin</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>70.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Web</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8273</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>2639.644171</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>88731</td>\n",
       "      <td>Rur</td>\n",
       "      <td>Mar</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>72.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8274</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>8085.448545</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>61409</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Mar</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>80.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Special Auto</td>\n",
       "      <td>Web</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8275</th>\n",
       "      <td>California</td>\n",
       "      <td>12316.796980</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>167.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>40.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8276</th>\n",
       "      <td>Nevada</td>\n",
       "      <td>5568.947534</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Extended</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>53.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8277</th>\n",
       "      <td>California</td>\n",
       "      <td>3571.828310</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>74931</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Div</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>16.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8278</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>3350.244285</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>74770</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8279</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>2716.190293</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>81.00000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8280</th>\n",
       "      <td>California</td>\n",
       "      <td>38887.903400</td>\n",
       "      <td>No</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>44299</td>\n",
       "      <td>Rur</td>\n",
       "      <td>Mar</td>\n",
       "      <td>107.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>73.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8281</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>2272.447229</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8282</th>\n",
       "      <td>California</td>\n",
       "      <td>2849.252467</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Master</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>63326</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>34.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8283</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>5328.320299</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>F</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>42.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8284</th>\n",
       "      <td>California</td>\n",
       "      <td>4679.977728</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Disabled</td>\n",
       "      <td>F</td>\n",
       "      <td>21720</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>7.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8285</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>5345.201117</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>55571</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>135.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>46.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8286</th>\n",
       "      <td>California</td>\n",
       "      <td>2437.084486</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>College</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>34759</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>84.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8287</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>4637.544647</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Div</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>81.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8288</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>8804.584902</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>38638</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Mar</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>84.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Agent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8289</th>\n",
       "      <td>California</td>\n",
       "      <td>2438.689804</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>Bachelor</td>\n",
       "      <td>Employed</td>\n",
       "      <td>F</td>\n",
       "      <td>80927</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Sin</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>8.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8290</th>\n",
       "      <td>California</td>\n",
       "      <td>4736.347990</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Web</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8291</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>5608.155723</td>\n",
       "      <td>No</td>\n",
       "      <td>Basic</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Employed</td>\n",
       "      <td>M</td>\n",
       "      <td>81914</td>\n",
       "      <td>Urb</td>\n",
       "      <td>Mar</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>33.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>Corporate Auto</td>\n",
       "      <td>Branch</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8292</th>\n",
       "      <td>Oregon</td>\n",
       "      <td>6465.223746</td>\n",
       "      <td>No</td>\n",
       "      <td>Extended</td>\n",
       "      <td>High School or Below</td>\n",
       "      <td>Unemployed</td>\n",
       "      <td>M</td>\n",
       "      <td>0</td>\n",
       "      <td>Sub</td>\n",
       "      <td>Sin</td>\n",
       "      <td>92.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>24.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Personal Auto</td>\n",
       "      <td>Call Center</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8293 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           State  Customer Lifetime Value Response  Coverage  \\\n",
       "0     Washington              2763.519279       No     Basic   \n",
       "1        Arizona              6979.535903       No  Extended   \n",
       "2         Nevada             12887.431650       No   Premium   \n",
       "3     California              7645.861827       No     Basic   \n",
       "4     Washington              2813.692575       No     Basic   \n",
       "5         Oregon              8256.297800      Yes     Basic   \n",
       "6         Oregon              5380.898636       No     Basic   \n",
       "7        Arizona              7216.100311       No   Premium   \n",
       "8         Oregon             24127.504020      Yes     Basic   \n",
       "9         Oregon              7388.178085       No  Extended   \n",
       "10    California              4738.992022       No     Basic   \n",
       "11    California              8197.197078       No     Basic   \n",
       "12    California              8798.797003       No   Premium   \n",
       "13       Arizona              8819.018934      Yes     Basic   \n",
       "14    California              5384.431665       No     Basic   \n",
       "15        Oregon              7463.139377       No     Basic   \n",
       "16        Nevada              2566.867823       No     Basic   \n",
       "17    California              3945.241604       No     Basic   \n",
       "18        Oregon              5710.333115       No     Basic   \n",
       "19    California              8162.617053       No   Premium   \n",
       "20        Oregon              2872.051273       No     Basic   \n",
       "21    Washington              3041.791561       No  Extended   \n",
       "22       Arizona             24127.504020      Yes     Basic   \n",
       "23        Nevada              2450.190996       No     Basic   \n",
       "24    California              2392.107890       No     Basic   \n",
       "25        Oregon              5802.065978       No     Basic   \n",
       "26    California              3946.372085       No   Premium   \n",
       "27    Washington              5346.916576       No  Extended   \n",
       "28       Arizona             12902.560140       No   Premium   \n",
       "29        Oregon              3235.360468       No  Extended   \n",
       "...          ...                      ...      ...       ...   \n",
       "8263  California             11638.899470      Yes     Basic   \n",
       "8264  California              7376.795372       No     Basic   \n",
       "8265  California              7892.088107       No     Basic   \n",
       "8266  California             19160.989940      Yes  Extended   \n",
       "8267  Washington              5548.031892      Yes     Basic   \n",
       "8268     Arizona              8319.529200       No     Basic   \n",
       "8269     Arizona             13770.976180      Yes   Premium   \n",
       "8270  Washington              5225.253777       No     Basic   \n",
       "8271  California             16979.797570      Yes     Basic   \n",
       "8272      Oregon              7485.356469       No  Extended   \n",
       "8273      Oregon              2639.644171       No     Basic   \n",
       "8274      Oregon              8085.448545       No     Basic   \n",
       "8275  California             12316.796980       No   Premium   \n",
       "8276      Nevada              5568.947534      Yes  Extended   \n",
       "8277  California              3571.828310       No  Extended   \n",
       "8278      Oregon              3350.244285       No  Extended   \n",
       "8279     Arizona              2716.190293       No  Extended   \n",
       "8280  California             38887.903400       No   Premium   \n",
       "8281     Arizona              2272.447229       No     Basic   \n",
       "8282  California              2849.252467       No     Basic   \n",
       "8283      Oregon              5328.320299       No     Basic   \n",
       "8284  California              4679.977728       No  Extended   \n",
       "8285      Oregon              5345.201117       No  Extended   \n",
       "8286  California              2437.084486       No     Basic   \n",
       "8287     Arizona              4637.544647       No     Basic   \n",
       "8288      Oregon              8804.584902       No     Basic   \n",
       "8289  California              2438.689804       No     Basic   \n",
       "8290  California              4736.347990       No     Basic   \n",
       "8291     Arizona              5608.155723       No     Basic   \n",
       "8292      Oregon              6465.223746       No  Extended   \n",
       "\n",
       "                 Education EmploymentStatus Gender  Income Location Code  \\\n",
       "0                 Bachelor         Employed      F   56274           Sub   \n",
       "1                 Bachelor       Unemployed      F       0           Sub   \n",
       "2                 Bachelor         Employed      F   48767           Sub   \n",
       "3                 Bachelor       Unemployed      M       0           Sub   \n",
       "4                 Bachelor         Employed      M   43836           Rur   \n",
       "5                 Bachelor         Employed      F   62902           Rur   \n",
       "6                  College         Employed      F   55350           Sub   \n",
       "7                   Master       Unemployed      M       0           Urb   \n",
       "8                 Bachelor    Medical Leave      M   14072           Sub   \n",
       "9                 Bachelor         Employed      F   28812           Urb   \n",
       "10                 College       Unemployed      M       0           Sub   \n",
       "11                 College       Unemployed      F       0           Sub   \n",
       "12                  Master         Employed      M   77026           Urb   \n",
       "13    High School or Below         Employed      M   99845           Sub   \n",
       "14                 College         Employed      M   83689           Urb   \n",
       "15                Bachelor         Employed      F   24599           Rur   \n",
       "16    High School or Below    Medical Leave      M   25049           Sub   \n",
       "17                 College    Medical Leave      M   28855           Sub   \n",
       "18                 College         Employed      M   51148           Urb   \n",
       "19    High School or Below         Employed      F   66140           Sub   \n",
       "20    High School or Below         Employed      M   57749           Sub   \n",
       "21                Bachelor         Disabled      F   13789           Sub   \n",
       "22                Bachelor    Medical Leave      M   14072           Sub   \n",
       "23                Bachelor       Unemployed      F       0           Sub   \n",
       "24                Bachelor         Disabled      F   17870           Sub   \n",
       "25                 College         Employed      M   97541           Sub   \n",
       "26                Bachelor       Unemployed      F       0           Sub   \n",
       "27                  Master         Disabled      F   10511           Urb   \n",
       "28                 College         Employed      F   86584           Sub   \n",
       "29                  Master         Employed      F   75690           Sub   \n",
       "...                    ...              ...    ...     ...           ...   \n",
       "8263               College    Medical Leave      F   25370           Sub   \n",
       "8264              Bachelor       Unemployed      M       0           Sub   \n",
       "8265  High School or Below         Disabled      F   28672           Sub   \n",
       "8266                Master         Employed      F   22705           Sub   \n",
       "8267              Bachelor         Employed      M   67798           Sub   \n",
       "8268  High School or Below         Employed      M   61367           Sub   \n",
       "8269  High School or Below         Employed      F   59207           Sub   \n",
       "8270               College         Employed      F   67423           Urb   \n",
       "8271              Bachelor         Employed      M   35095           Sub   \n",
       "8272                Master         Employed      F   26380           Rur   \n",
       "8273               College         Employed      M   88731           Rur   \n",
       "8274              Bachelor         Employed      M   61409           Urb   \n",
       "8275              Bachelor       Unemployed      M       0           Sub   \n",
       "8276  High School or Below       Unemployed      M       0           Sub   \n",
       "8277              Bachelor         Employed      F   74931           Urb   \n",
       "8278               College         Employed      M   74770           Sub   \n",
       "8279              Bachelor       Unemployed      M       0           Sub   \n",
       "8280              Bachelor         Employed      F   44299           Rur   \n",
       "8281               College       Unemployed      M       0           Sub   \n",
       "8282                Master         Employed      M   63326           Sub   \n",
       "8283  High School or Below       Unemployed      F       0           Sub   \n",
       "8284  High School or Below         Disabled      F   21720           Sub   \n",
       "8285               College         Employed      M   55571           Sub   \n",
       "8286               College         Employed      M   34759           Sub   \n",
       "8287  High School or Below       Unemployed      M       0           Sub   \n",
       "8288              Bachelor         Employed      M   38638           Sub   \n",
       "8289              Bachelor         Employed      F   80927           Urb   \n",
       "8290  High School or Below       Unemployed      M       0           Sub   \n",
       "8291  High School or Below         Employed      M   81914           Urb   \n",
       "8292  High School or Below       Unemployed      M       0           Sub   \n",
       "\n",
       "     Marital Status  Monthly Premium Auto  Months Since Last Claim  \\\n",
       "0               Mar             93.196573                32.000000   \n",
       "1               Sin             93.196573                13.000000   \n",
       "2               Mar            108.000000                15.077925   \n",
       "3               Mar            106.000000                18.000000   \n",
       "4               Sin             73.000000                12.000000   \n",
       "5               Mar             69.000000                14.000000   \n",
       "6               Mar             67.000000                 0.000000   \n",
       "7               Sin            101.000000                 0.000000   \n",
       "8               Div             71.000000                13.000000   \n",
       "9               Mar             93.000000                17.000000   \n",
       "10              Sin             67.000000                15.077925   \n",
       "11              Mar            110.000000                27.000000   \n",
       "12              Mar            110.000000                 9.000000   \n",
       "13              Mar            110.000000                23.000000   \n",
       "14              Sin             70.000000                21.000000   \n",
       "15              Mar             64.000000                12.000000   \n",
       "16              Mar             67.000000                14.000000   \n",
       "17              Mar            101.000000                12.000000   \n",
       "18              Mar             93.196573                 9.000000   \n",
       "19              Mar            101.000000                11.000000   \n",
       "20              Sin             93.196573                31.000000   \n",
       "21              Div             93.196573                 8.000000   \n",
       "22              Div             71.000000                13.000000   \n",
       "23              Sin             73.000000                 4.000000   \n",
       "24              Mar             61.000000                30.000000   \n",
       "25              Mar             72.000000                22.000000   \n",
       "26              Sin             93.196573                15.000000   \n",
       "27              Mar            139.000000                33.000000   \n",
       "28              Sin            111.000000                33.000000   \n",
       "29              Mar             80.000000                15.077925   \n",
       "...             ...                   ...                      ...   \n",
       "8263            Mar            102.000000                10.000000   \n",
       "8264            Sin            105.000000                31.000000   \n",
       "8265            Div             71.000000                14.000000   \n",
       "8266            Div            239.000000                19.000000   \n",
       "8267            Div             69.000000                 1.000000   \n",
       "8268            Div             70.000000                 7.000000   \n",
       "8269            Sin            116.000000                23.000000   \n",
       "8270            Mar             65.000000                24.000000   \n",
       "8271            Div             73.000000                25.000000   \n",
       "8272            Sin             96.000000                29.000000   \n",
       "8273            Mar             66.000000                10.000000   \n",
       "8274            Mar             68.000000                30.000000   \n",
       "8275            Mar            167.000000                30.000000   \n",
       "8276            Sin             79.000000                21.000000   \n",
       "8277            Div             89.000000                13.000000   \n",
       "8278            Sin             86.000000                23.000000   \n",
       "8279            Mar             95.000000                14.000000   \n",
       "8280            Mar            107.000000                 0.000000   \n",
       "8281            Sin             71.000000                22.000000   \n",
       "8282            Div             72.000000                 2.000000   \n",
       "8283            Sin             73.000000                12.000000   \n",
       "8284            Sin            128.000000                 5.000000   \n",
       "8285            Mar            135.000000                 4.000000   \n",
       "8286            Div             61.000000                30.000000   \n",
       "8287            Div             68.000000                18.000000   \n",
       "8288            Mar             74.000000                 5.000000   \n",
       "8289            Sin             62.000000                25.000000   \n",
       "8290            Sin             65.000000                33.000000   \n",
       "8291            Mar             70.000000                 6.000000   \n",
       "8292            Sin             92.000000                 9.000000   \n",
       "\n",
       "      Months Since Policy Inception  Number of Open Complaints  \\\n",
       "0                           5.00000                   0.389626   \n",
       "1                          42.00000                   0.389626   \n",
       "2                          38.00000                   0.000000   \n",
       "3                          65.00000                   0.000000   \n",
       "4                          44.00000                   0.000000   \n",
       "5                          94.00000                   0.000000   \n",
       "6                          13.00000                   0.000000   \n",
       "7                          68.00000                   0.000000   \n",
       "8                           3.00000                   0.000000   \n",
       "9                          48.14515                   0.000000   \n",
       "10                          5.00000                   0.000000   \n",
       "11                         87.00000                   0.000000   \n",
       "12                         48.14515                   2.000000   \n",
       "13                         25.00000                   1.000000   \n",
       "14                         48.14515                   2.000000   \n",
       "15                         50.00000                   1.000000   \n",
       "16                          7.00000                   0.000000   \n",
       "17                         59.00000                   0.000000   \n",
       "18                          1.00000                   0.389626   \n",
       "19                         21.00000                   0.000000   \n",
       "20                         21.00000                   0.000000   \n",
       "21                         49.00000                   0.000000   \n",
       "22                          3.00000                   0.000000   \n",
       "23                         44.00000                   3.000000   \n",
       "24                         91.00000                   0.000000   \n",
       "25                          1.00000                   0.000000   \n",
       "26                         47.00000                   0.000000   \n",
       "27                         48.14515                   0.000000   \n",
       "28                         54.00000                   2.000000   \n",
       "29                         44.00000                   1.000000   \n",
       "...                             ...                        ...   \n",
       "8263                       77.00000                   0.000000   \n",
       "8264                       85.00000                   0.000000   \n",
       "8265                       34.00000                   0.000000   \n",
       "8266                       59.00000                   0.000000   \n",
       "8267                       78.00000                   0.000000   \n",
       "8268                       85.00000                   0.000000   \n",
       "8269                       21.00000                   0.000000   \n",
       "8270                        0.00000                   0.000000   \n",
       "8271                       56.00000                   0.000000   \n",
       "8272                       70.00000                   0.000000   \n",
       "8273                       72.00000                   0.000000   \n",
       "8274                       80.00000                   0.000000   \n",
       "8275                       40.00000                   0.000000   \n",
       "8276                       53.00000                   1.000000   \n",
       "8277                       16.00000                   0.000000   \n",
       "8278                       10.00000                   0.000000   \n",
       "8279                       81.00000                   5.000000   \n",
       "8280                       73.00000                   0.000000   \n",
       "8281                       10.00000                   1.000000   \n",
       "8282                       34.00000                   0.000000   \n",
       "8283                       42.00000                   0.000000   \n",
       "8284                        7.00000                   0.000000   \n",
       "8285                       46.00000                   0.000000   \n",
       "8286                       84.00000                   0.000000   \n",
       "8287                       81.00000                   0.000000   \n",
       "8288                       84.00000                   0.000000   \n",
       "8289                        8.00000                   0.000000   \n",
       "8290                        1.00000                   0.000000   \n",
       "8291                       33.00000                   0.000000   \n",
       "8292                       24.00000                   0.000000   \n",
       "\n",
       "      Number of Policies     Policy Type Sales Channel  \n",
       "0               1.000000  Corporate Auto         Agent  \n",
       "1               8.000000   Personal Auto         Agent  \n",
       "2               2.000000   Personal Auto         Agent  \n",
       "3               7.000000  Corporate Auto   Call Center  \n",
       "4               1.000000   Personal Auto         Agent  \n",
       "5               2.000000   Personal Auto           Web  \n",
       "6               9.000000  Corporate Auto         Agent  \n",
       "7               4.000000  Corporate Auto         Agent  \n",
       "8               2.000000  Corporate Auto         Agent  \n",
       "9               8.000000    Special Auto        Branch  \n",
       "10              3.000000   Personal Auto         Agent  \n",
       "11              3.000000   Personal Auto         Agent  \n",
       "12              3.000000  Corporate Auto         Agent  \n",
       "13              2.965259  Corporate Auto        Branch  \n",
       "14              8.000000  Corporate Auto   Call Center  \n",
       "15              2.965259  Corporate Auto        Branch  \n",
       "16              1.000000   Personal Auto   Call Center  \n",
       "17              1.000000   Personal Auto   Call Center  \n",
       "18              7.000000   Personal Auto        Branch  \n",
       "19              3.000000  Corporate Auto   Call Center  \n",
       "20              1.000000   Personal Auto        Branch  \n",
       "21              1.000000   Personal Auto   Call Center  \n",
       "22              2.000000   Personal Auto         Agent  \n",
       "23              1.000000  Corporate Auto        Branch  \n",
       "24              1.000000  Corporate Auto        Branch  \n",
       "25              3.000000   Personal Auto   Call Center  \n",
       "26              1.000000   Personal Auto         Agent  \n",
       "27              1.000000  Corporate Auto        Branch  \n",
       "28              2.965259   Personal Auto   Call Center  \n",
       "29              1.000000   Personal Auto        Branch  \n",
       "...                  ...             ...           ...  \n",
       "8263            2.000000   Personal Auto        Branch  \n",
       "8264            5.000000  Corporate Auto         Agent  \n",
       "8265            2.000000   Personal Auto        Branch  \n",
       "8266            7.000000   Personal Auto         Agent  \n",
       "8267            9.000000  Corporate Auto         Agent  \n",
       "8268            2.000000   Personal Auto        Branch  \n",
       "8269            2.000000   Personal Auto         Agent  \n",
       "8270            9.000000  Corporate Auto         Agent  \n",
       "8271            2.000000  Corporate Auto   Call Center  \n",
       "8272            4.000000   Personal Auto           Web  \n",
       "8273            1.000000   Personal Auto         Agent  \n",
       "8274            2.000000    Special Auto           Web  \n",
       "8275            5.000000   Personal Auto        Branch  \n",
       "8276            7.000000  Corporate Auto         Agent  \n",
       "8277            1.000000   Personal Auto         Agent  \n",
       "8278            1.000000   Personal Auto        Branch  \n",
       "8279            1.000000  Corporate Auto   Call Center  \n",
       "8280            2.000000   Personal Auto        Branch  \n",
       "8281            1.000000   Personal Auto   Call Center  \n",
       "8282            1.000000   Personal Auto   Call Center  \n",
       "8283            7.000000   Personal Auto        Branch  \n",
       "8284            1.000000  Corporate Auto        Branch  \n",
       "8285            1.000000   Personal Auto         Agent  \n",
       "8286            1.000000   Personal Auto         Agent  \n",
       "8287            3.000000   Personal Auto   Call Center  \n",
       "8288            2.000000   Personal Auto         Agent  \n",
       "8289            1.000000   Personal Auto        Branch  \n",
       "8290            3.000000   Personal Auto           Web  \n",
       "8291            6.000000  Corporate Auto        Branch  \n",
       "8292            3.000000   Personal Auto   Call Center  \n",
       "\n",
       "[8293 rows x 17 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.drop(data.columns[[0, 6]], axis=1, inplace=True)\n",
    "display(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Исходные переменные:\n",
      " ['State', 'Customer Lifetime Value', 'Response', 'Coverage', 'Education', 'EmploymentStatus', 'Gender', 'Income', 'Location Code', 'Marital Status', 'Monthly Premium Auto', 'Months Since Last Claim', 'Months Since Policy Inception', 'Number of Open Complaints', 'Number of Policies', 'Policy Type', 'Sales Channel'] \n",
      "\n",
      "Переменные после get_dummies:\n",
      " ['Customer Lifetime Value', 'Income', 'Monthly Premium Auto', 'Months Since Last Claim', 'Months Since Policy Inception', 'Number of Open Complaints', 'Number of Policies', 'State_Arizona', 'State_California', 'State_Nevada', 'State_Oregon', 'State_Washington', 'Response_No', 'Response_Yes', 'Coverage_Basic', 'Coverage_Extended', 'Coverage_Premium', 'Education_Bachelor', 'Education_College', 'Education_Doctor', 'Education_High School or Below', 'Education_Master', 'EmploymentStatus_Disabled', 'EmploymentStatus_Employed', 'EmploymentStatus_Medical Leave', 'EmploymentStatus_Retired', 'EmploymentStatus_Unemployed', 'Gender_F', 'Gender_M', 'Location Code_Rur', 'Location Code_Sub', 'Location Code_Urb', 'Marital Status_Div', 'Marital Status_Mar', 'Marital Status_Sin', 'Policy Type_Corporate Auto', 'Policy Type_Personal Auto', 'Policy Type_Special Auto', 'Sales Channel_Agent', 'Sales Channel_Branch', 'Sales Channel_Call Center', 'Sales Channel_Web']\n"
     ]
    }
   ],
   "source": [
    "print(\"Исходные переменные:\\n\", list(data.columns), \"\\n\")\n",
    "data_dummies = pd.get_dummies(data)\n",
    "print(\"Переменные после get_dummies:\\n\", list(data_dummies.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer Lifetime Value</th>\n",
       "      <th>Income</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
       "      <th>Months Since Last Claim</th>\n",
       "      <th>Months Since Policy Inception</th>\n",
       "      <th>Number of Open Complaints</th>\n",
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       "      <th>State_California</th>\n",
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       "      <th>EmploymentStatus_Disabled</th>\n",
       "      <th>EmploymentStatus_Employed</th>\n",
       "      <th>EmploymentStatus_Medical Leave</th>\n",
       "      <th>EmploymentStatus_Retired</th>\n",
       "      <th>EmploymentStatus_Unemployed</th>\n",
       "      <th>Gender_F</th>\n",
       "      <th>Gender_M</th>\n",
       "      <th>Location Code_Rur</th>\n",
       "      <th>Location Code_Sub</th>\n",
       "      <th>Location Code_Urb</th>\n",
       "      <th>Marital Status_Div</th>\n",
       "      <th>Marital Status_Mar</th>\n",
       "      <th>Marital Status_Sin</th>\n",
       "      <th>Policy Type_Corporate Auto</th>\n",
       "      <th>Policy Type_Personal Auto</th>\n",
       "      <th>Policy Type_Special Auto</th>\n",
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       "      <th>1</th>\n",
       "      <td>6979.535903</td>\n",
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       "    <tr>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8256.297800</td>\n",
       "      <td>62902</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>94.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5380.898636</td>\n",
       "      <td>55350</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>13.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7216.100311</td>\n",
       "      <td>0</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>68.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>24127.504020</td>\n",
       "      <td>14072</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7388.178085</td>\n",
       "      <td>28812</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4738.992022</td>\n",
       "      <td>0</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>5.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>8197.197078</td>\n",
       "      <td>0</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>87.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>8798.797003</td>\n",
       "      <td>77026</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>8819.018934</td>\n",
       "      <td>99845</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>25.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.965259</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5384.431665</td>\n",
       "      <td>83689</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7463.139377</td>\n",
       "      <td>24599</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>50.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.965259</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2566.867823</td>\n",
       "      <td>25049</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>7.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>3945.241604</td>\n",
       "      <td>28855</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>59.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>5710.333115</td>\n",
       "      <td>51148</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>8162.617053</td>\n",
       "      <td>66140</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2872.051273</td>\n",
       "      <td>57749</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>3041.791561</td>\n",
       "      <td>13789</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>49.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>24127.504020</td>\n",
       "      <td>14072</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2450.190996</td>\n",
       "      <td>0</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>44.00000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2392.107890</td>\n",
       "      <td>17870</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>91.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>5802.065978</td>\n",
       "      <td>97541</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>3946.372085</td>\n",
       "      <td>0</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>47.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>5346.916576</td>\n",
       "      <td>10511</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>12902.560140</td>\n",
       "      <td>86584</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>54.00000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.965259</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>3235.360468</td>\n",
       "      <td>75690</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>44.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8263</th>\n",
       "      <td>11638.899470</td>\n",
       "      <td>25370</td>\n",
       "      <td>102.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>77.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8264</th>\n",
       "      <td>7376.795372</td>\n",
       "      <td>0</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>85.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8265</th>\n",
       "      <td>7892.088107</td>\n",
       "      <td>28672</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>34.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8266</th>\n",
       "      <td>19160.989940</td>\n",
       "      <td>22705</td>\n",
       "      <td>239.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>59.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8267</th>\n",
       "      <td>5548.031892</td>\n",
       "      <td>67798</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>78.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8268</th>\n",
       "      <td>8319.529200</td>\n",
       "      <td>61367</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>85.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8269</th>\n",
       "      <td>13770.976180</td>\n",
       "      <td>59207</td>\n",
       "      <td>116.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8270</th>\n",
       "      <td>5225.253777</td>\n",
       "      <td>67423</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8271</th>\n",
       "      <td>16979.797570</td>\n",
       "      <td>35095</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>56.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8272</th>\n",
       "      <td>7485.356469</td>\n",
       "      <td>26380</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>70.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8273</th>\n",
       "      <td>2639.644171</td>\n",
       "      <td>88731</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>72.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8274</th>\n",
       "      <td>8085.448545</td>\n",
       "      <td>61409</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>80.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8275</th>\n",
       "      <td>12316.796980</td>\n",
       "      <td>0</td>\n",
       "      <td>167.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>40.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8276</th>\n",
       "      <td>5568.947534</td>\n",
       "      <td>0</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>53.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8277</th>\n",
       "      <td>3571.828310</td>\n",
       "      <td>74931</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>16.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8278</th>\n",
       "      <td>3350.244285</td>\n",
       "      <td>74770</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8279</th>\n",
       "      <td>2716.190293</td>\n",
       "      <td>0</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>81.00000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8280</th>\n",
       "      <td>38887.903400</td>\n",
       "      <td>44299</td>\n",
       "      <td>107.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>73.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8281</th>\n",
       "      <td>2272.447229</td>\n",
       "      <td>0</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8282</th>\n",
       "      <td>2849.252467</td>\n",
       "      <td>63326</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>34.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8283</th>\n",
       "      <td>5328.320299</td>\n",
       "      <td>0</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>42.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8284</th>\n",
       "      <td>4679.977728</td>\n",
       "      <td>21720</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>7.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8285</th>\n",
       "      <td>5345.201117</td>\n",
       "      <td>55571</td>\n",
       "      <td>135.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>46.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8286</th>\n",
       "      <td>2437.084486</td>\n",
       "      <td>34759</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>84.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8287</th>\n",
       "      <td>4637.544647</td>\n",
       "      <td>0</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>81.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8288</th>\n",
       "      <td>8804.584902</td>\n",
       "      <td>38638</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>84.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8289</th>\n",
       "      <td>2438.689804</td>\n",
       "      <td>80927</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>8.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8290</th>\n",
       "      <td>4736.347990</td>\n",
       "      <td>0</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8291</th>\n",
       "      <td>5608.155723</td>\n",
       "      <td>81914</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>33.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8292</th>\n",
       "      <td>6465.223746</td>\n",
       "      <td>0</td>\n",
       "      <td>92.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>24.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8293 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Customer Lifetime Value  Income  Monthly Premium Auto  \\\n",
       "0                 2763.519279   56274             93.196573   \n",
       "1                 6979.535903       0             93.196573   \n",
       "2                12887.431650   48767            108.000000   \n",
       "3                 7645.861827       0            106.000000   \n",
       "4                 2813.692575   43836             73.000000   \n",
       "5                 8256.297800   62902             69.000000   \n",
       "6                 5380.898636   55350             67.000000   \n",
       "7                 7216.100311       0            101.000000   \n",
       "8                24127.504020   14072             71.000000   \n",
       "9                 7388.178085   28812             93.000000   \n",
       "10                4738.992022       0             67.000000   \n",
       "11                8197.197078       0            110.000000   \n",
       "12                8798.797003   77026            110.000000   \n",
       "13                8819.018934   99845            110.000000   \n",
       "14                5384.431665   83689             70.000000   \n",
       "15                7463.139377   24599             64.000000   \n",
       "16                2566.867823   25049             67.000000   \n",
       "17                3945.241604   28855            101.000000   \n",
       "18                5710.333115   51148             93.196573   \n",
       "19                8162.617053   66140            101.000000   \n",
       "20                2872.051273   57749             93.196573   \n",
       "21                3041.791561   13789             93.196573   \n",
       "22               24127.504020   14072             71.000000   \n",
       "23                2450.190996       0             73.000000   \n",
       "24                2392.107890   17870             61.000000   \n",
       "25                5802.065978   97541             72.000000   \n",
       "26                3946.372085       0             93.196573   \n",
       "27                5346.916576   10511            139.000000   \n",
       "28               12902.560140   86584            111.000000   \n",
       "29                3235.360468   75690             80.000000   \n",
       "...                       ...     ...                   ...   \n",
       "8263             11638.899470   25370            102.000000   \n",
       "8264              7376.795372       0            105.000000   \n",
       "8265              7892.088107   28672             71.000000   \n",
       "8266             19160.989940   22705            239.000000   \n",
       "8267              5548.031892   67798             69.000000   \n",
       "8268              8319.529200   61367             70.000000   \n",
       "8269             13770.976180   59207            116.000000   \n",
       "8270              5225.253777   67423             65.000000   \n",
       "8271             16979.797570   35095             73.000000   \n",
       "8272              7485.356469   26380             96.000000   \n",
       "8273              2639.644171   88731             66.000000   \n",
       "8274              8085.448545   61409             68.000000   \n",
       "8275             12316.796980       0            167.000000   \n",
       "8276              5568.947534       0             79.000000   \n",
       "8277              3571.828310   74931             89.000000   \n",
       "8278              3350.244285   74770             86.000000   \n",
       "8279              2716.190293       0             95.000000   \n",
       "8280             38887.903400   44299            107.000000   \n",
       "8281              2272.447229       0             71.000000   \n",
       "8282              2849.252467   63326             72.000000   \n",
       "8283              5328.320299       0             73.000000   \n",
       "8284              4679.977728   21720            128.000000   \n",
       "8285              5345.201117   55571            135.000000   \n",
       "8286              2437.084486   34759             61.000000   \n",
       "8287              4637.544647       0             68.000000   \n",
       "8288              8804.584902   38638             74.000000   \n",
       "8289              2438.689804   80927             62.000000   \n",
       "8290              4736.347990       0             65.000000   \n",
       "8291              5608.155723   81914             70.000000   \n",
       "8292              6465.223746       0             92.000000   \n",
       "\n",
       "      Months Since Last Claim  Months Since Policy Inception  \\\n",
       "0                   32.000000                        5.00000   \n",
       "1                   13.000000                       42.00000   \n",
       "2                   15.077925                       38.00000   \n",
       "3                   18.000000                       65.00000   \n",
       "4                   12.000000                       44.00000   \n",
       "5                   14.000000                       94.00000   \n",
       "6                    0.000000                       13.00000   \n",
       "7                    0.000000                       68.00000   \n",
       "8                   13.000000                        3.00000   \n",
       "9                   17.000000                       48.14515   \n",
       "10                  15.077925                        5.00000   \n",
       "11                  27.000000                       87.00000   \n",
       "12                   9.000000                       48.14515   \n",
       "13                  23.000000                       25.00000   \n",
       "14                  21.000000                       48.14515   \n",
       "15                  12.000000                       50.00000   \n",
       "16                  14.000000                        7.00000   \n",
       "17                  12.000000                       59.00000   \n",
       "18                   9.000000                        1.00000   \n",
       "19                  11.000000                       21.00000   \n",
       "20                  31.000000                       21.00000   \n",
       "21                   8.000000                       49.00000   \n",
       "22                  13.000000                        3.00000   \n",
       "23                   4.000000                       44.00000   \n",
       "24                  30.000000                       91.00000   \n",
       "25                  22.000000                        1.00000   \n",
       "26                  15.000000                       47.00000   \n",
       "27                  33.000000                       48.14515   \n",
       "28                  33.000000                       54.00000   \n",
       "29                  15.077925                       44.00000   \n",
       "...                       ...                            ...   \n",
       "8263                10.000000                       77.00000   \n",
       "8264                31.000000                       85.00000   \n",
       "8265                14.000000                       34.00000   \n",
       "8266                19.000000                       59.00000   \n",
       "8267                 1.000000                       78.00000   \n",
       "8268                 7.000000                       85.00000   \n",
       "8269                23.000000                       21.00000   \n",
       "8270                24.000000                        0.00000   \n",
       "8271                25.000000                       56.00000   \n",
       "8272                29.000000                       70.00000   \n",
       "8273                10.000000                       72.00000   \n",
       "8274                30.000000                       80.00000   \n",
       "8275                30.000000                       40.00000   \n",
       "8276                21.000000                       53.00000   \n",
       "8277                13.000000                       16.00000   \n",
       "8278                23.000000                       10.00000   \n",
       "8279                14.000000                       81.00000   \n",
       "8280                 0.000000                       73.00000   \n",
       "8281                22.000000                       10.00000   \n",
       "8282                 2.000000                       34.00000   \n",
       "8283                12.000000                       42.00000   \n",
       "8284                 5.000000                        7.00000   \n",
       "8285                 4.000000                       46.00000   \n",
       "8286                30.000000                       84.00000   \n",
       "8287                18.000000                       81.00000   \n",
       "8288                 5.000000                       84.00000   \n",
       "8289                25.000000                        8.00000   \n",
       "8290                33.000000                        1.00000   \n",
       "8291                 6.000000                       33.00000   \n",
       "8292                 9.000000                       24.00000   \n",
       "\n",
       "      Number of Open Complaints  Number of Policies  State_Arizona  \\\n",
       "0                      0.389626            1.000000              0   \n",
       "1                      0.389626            8.000000              1   \n",
       "2                      0.000000            2.000000              0   \n",
       "3                      0.000000            7.000000              0   \n",
       "4                      0.000000            1.000000              0   \n",
       "5                      0.000000            2.000000              0   \n",
       "6                      0.000000            9.000000              0   \n",
       "7                      0.000000            4.000000              1   \n",
       "8                      0.000000            2.000000              0   \n",
       "9                      0.000000            8.000000              0   \n",
       "10                     0.000000            3.000000              0   \n",
       "11                     0.000000            3.000000              0   \n",
       "12                     2.000000            3.000000              0   \n",
       "13                     1.000000            2.965259              1   \n",
       "14                     2.000000            8.000000              0   \n",
       "15                     1.000000            2.965259              0   \n",
       "16                     0.000000            1.000000              0   \n",
       "17                     0.000000            1.000000              0   \n",
       "18                     0.389626            7.000000              0   \n",
       "19                     0.000000            3.000000              0   \n",
       "20                     0.000000            1.000000              0   \n",
       "21                     0.000000            1.000000              0   \n",
       "22                     0.000000            2.000000              1   \n",
       "23                     3.000000            1.000000              0   \n",
       "24                     0.000000            1.000000              0   \n",
       "25                     0.000000            3.000000              0   \n",
       "26                     0.000000            1.000000              0   \n",
       "27                     0.000000            1.000000              0   \n",
       "28                     2.000000            2.965259              1   \n",
       "29                     1.000000            1.000000              0   \n",
       "...                         ...                 ...            ...   \n",
       "8263                   0.000000            2.000000              0   \n",
       "8264                   0.000000            5.000000              0   \n",
       "8265                   0.000000            2.000000              0   \n",
       "8266                   0.000000            7.000000              0   \n",
       "8267                   0.000000            9.000000              0   \n",
       "8268                   0.000000            2.000000              1   \n",
       "8269                   0.000000            2.000000              1   \n",
       "8270                   0.000000            9.000000              0   \n",
       "8271                   0.000000            2.000000              0   \n",
       "8272                   0.000000            4.000000              0   \n",
       "8273                   0.000000            1.000000              0   \n",
       "8274                   0.000000            2.000000              0   \n",
       "8275                   0.000000            5.000000              0   \n",
       "8276                   1.000000            7.000000              0   \n",
       "8277                   0.000000            1.000000              0   \n",
       "8278                   0.000000            1.000000              0   \n",
       "8279                   5.000000            1.000000              1   \n",
       "8280                   0.000000            2.000000              0   \n",
       "8281                   1.000000            1.000000              1   \n",
       "8282                   0.000000            1.000000              0   \n",
       "8283                   0.000000            7.000000              0   \n",
       "8284                   0.000000            1.000000              0   \n",
       "8285                   0.000000            1.000000              0   \n",
       "8286                   0.000000            1.000000              0   \n",
       "8287                   0.000000            3.000000              1   \n",
       "8288                   0.000000            2.000000              0   \n",
       "8289                   0.000000            1.000000              0   \n",
       "8290                   0.000000            3.000000              0   \n",
       "8291                   0.000000            6.000000              1   \n",
       "8292                   0.000000            3.000000              0   \n",
       "\n",
       "      State_California  State_Nevada  State_Oregon  State_Washington  \\\n",
       "0                    0             0             0                 1   \n",
       "1                    0             0             0                 0   \n",
       "2                    0             1             0                 0   \n",
       "3                    1             0             0                 0   \n",
       "4                    0             0             0                 1   \n",
       "5                    0             0             1                 0   \n",
       "6                    0             0             1                 0   \n",
       "7                    0             0             0                 0   \n",
       "8                    0             0             1                 0   \n",
       "9                    0             0             1                 0   \n",
       "10                   1             0             0                 0   \n",
       "11                   1             0             0                 0   \n",
       "12                   1             0             0                 0   \n",
       "13                   0             0             0                 0   \n",
       "14                   1             0             0                 0   \n",
       "15                   0             0             1                 0   \n",
       "16                   0             1             0                 0   \n",
       "17                   1             0             0                 0   \n",
       "18                   0             0             1                 0   \n",
       "19                   1             0             0                 0   \n",
       "20                   0             0             1                 0   \n",
       "21                   0             0             0                 1   \n",
       "22                   0             0             0                 0   \n",
       "23                   0             1             0                 0   \n",
       "24                   1             0             0                 0   \n",
       "25                   0             0             1                 0   \n",
       "26                   1             0             0                 0   \n",
       "27                   0             0             0                 1   \n",
       "28                   0             0             0                 0   \n",
       "29                   0             0             1                 0   \n",
       "...                ...           ...           ...               ...   \n",
       "8263                 1             0             0                 0   \n",
       "8264                 1             0             0                 0   \n",
       "8265                 1             0             0                 0   \n",
       "8266                 1             0             0                 0   \n",
       "8267                 0             0             0                 1   \n",
       "8268                 0             0             0                 0   \n",
       "8269                 0             0             0                 0   \n",
       "8270                 0             0             0                 1   \n",
       "8271                 1             0             0                 0   \n",
       "8272                 0             0             1                 0   \n",
       "8273                 0             0             1                 0   \n",
       "8274                 0             0             1                 0   \n",
       "8275                 1             0             0                 0   \n",
       "8276                 0             1             0                 0   \n",
       "8277                 1             0             0                 0   \n",
       "8278                 0             0             1                 0   \n",
       "8279                 0             0             0                 0   \n",
       "8280                 1             0             0                 0   \n",
       "8281                 0             0             0                 0   \n",
       "8282                 1             0             0                 0   \n",
       "8283                 0             0             1                 0   \n",
       "8284                 1             0             0                 0   \n",
       "8285                 0             0             1                 0   \n",
       "8286                 1             0             0                 0   \n",
       "8287                 0             0             0                 0   \n",
       "8288                 0             0             1                 0   \n",
       "8289                 1             0             0                 0   \n",
       "8290                 1             0             0                 0   \n",
       "8291                 0             0             0                 0   \n",
       "8292                 0             0             1                 0   \n",
       "\n",
       "      Response_No  Response_Yes  Coverage_Basic  Coverage_Extended  \\\n",
       "0               1             0               1                  0   \n",
       "1               1             0               0                  1   \n",
       "2               1             0               0                  0   \n",
       "3               1             0               1                  0   \n",
       "4               1             0               1                  0   \n",
       "5               0             1               1                  0   \n",
       "6               1             0               1                  0   \n",
       "7               1             0               0                  0   \n",
       "8               0             1               1                  0   \n",
       "9               1             0               0                  1   \n",
       "10              1             0               1                  0   \n",
       "11              1             0               1                  0   \n",
       "12              1             0               0                  0   \n",
       "13              0             1               1                  0   \n",
       "14              1             0               1                  0   \n",
       "15              1             0               1                  0   \n",
       "16              1             0               1                  0   \n",
       "17              1             0               1                  0   \n",
       "18              1             0               1                  0   \n",
       "19              1             0               0                  0   \n",
       "20              1             0               1                  0   \n",
       "21              1             0               0                  1   \n",
       "22              0             1               1                  0   \n",
       "23              1             0               1                  0   \n",
       "24              1             0               1                  0   \n",
       "25              1             0               1                  0   \n",
       "26              1             0               0                  0   \n",
       "27              1             0               0                  1   \n",
       "28              1             0               0                  0   \n",
       "29              1             0               0                  1   \n",
       "...           ...           ...             ...                ...   \n",
       "8263            0             1               1                  0   \n",
       "8264            1             0               1                  0   \n",
       "8265            1             0               1                  0   \n",
       "8266            0             1               0                  1   \n",
       "8267            0             1               1                  0   \n",
       "8268            1             0               1                  0   \n",
       "8269            0             1               0                  0   \n",
       "8270            1             0               1                  0   \n",
       "8271            0             1               1                  0   \n",
       "8272            1             0               0                  1   \n",
       "8273            1             0               1                  0   \n",
       "8274            1             0               1                  0   \n",
       "8275            1             0               0                  0   \n",
       "8276            0             1               0                  1   \n",
       "8277            1             0               0                  1   \n",
       "8278            1             0               0                  1   \n",
       "8279            1             0               0                  1   \n",
       "8280            1             0               0                  0   \n",
       "8281            1             0               1                  0   \n",
       "8282            1             0               1                  0   \n",
       "8283            1             0               1                  0   \n",
       "8284            1             0               0                  1   \n",
       "8285            1             0               0                  1   \n",
       "8286            1             0               1                  0   \n",
       "8287            1             0               1                  0   \n",
       "8288            1             0               1                  0   \n",
       "8289            1             0               1                  0   \n",
       "8290            1             0               1                  0   \n",
       "8291            1             0               1                  0   \n",
       "8292            1             0               0                  1   \n",
       "\n",
       "      Coverage_Premium  Education_Bachelor  Education_College  \\\n",
       "0                    0                   1                  0   \n",
       "1                    0                   1                  0   \n",
       "2                    1                   1                  0   \n",
       "3                    0                   1                  0   \n",
       "4                    0                   1                  0   \n",
       "5                    0                   1                  0   \n",
       "6                    0                   0                  1   \n",
       "7                    1                   0                  0   \n",
       "8                    0                   1                  0   \n",
       "9                    0                   1                  0   \n",
       "10                   0                   0                  1   \n",
       "11                   0                   0                  1   \n",
       "12                   1                   0                  0   \n",
       "13                   0                   0                  0   \n",
       "14                   0                   0                  1   \n",
       "15                   0                   1                  0   \n",
       "16                   0                   0                  0   \n",
       "17                   0                   0                  1   \n",
       "18                   0                   0                  1   \n",
       "19                   1                   0                  0   \n",
       "20                   0                   0                  0   \n",
       "21                   0                   1                  0   \n",
       "22                   0                   1                  0   \n",
       "23                   0                   1                  0   \n",
       "24                   0                   1                  0   \n",
       "25                   0                   0                  1   \n",
       "26                   1                   1                  0   \n",
       "27                   0                   0                  0   \n",
       "28                   1                   0                  1   \n",
       "29                   0                   0                  0   \n",
       "...                ...                 ...                ...   \n",
       "8263                 0                   0                  1   \n",
       "8264                 0                   1                  0   \n",
       "8265                 0                   0                  0   \n",
       "8266                 0                   0                  0   \n",
       "8267                 0                   1                  0   \n",
       "8268                 0                   0                  0   \n",
       "8269                 1                   0                  0   \n",
       "8270                 0                   0                  1   \n",
       "8271                 0                   1                  0   \n",
       "8272                 0                   0                  0   \n",
       "8273                 0                   0                  1   \n",
       "8274                 0                   1                  0   \n",
       "8275                 1                   1                  0   \n",
       "8276                 0                   0                  0   \n",
       "8277                 0                   1                  0   \n",
       "8278                 0                   0                  1   \n",
       "8279                 0                   1                  0   \n",
       "8280                 1                   1                  0   \n",
       "8281                 0                   0                  1   \n",
       "8282                 0                   0                  0   \n",
       "8283                 0                   0                  0   \n",
       "8284                 0                   0                  0   \n",
       "8285                 0                   0                  1   \n",
       "8286                 0                   0                  1   \n",
       "8287                 0                   0                  0   \n",
       "8288                 0                   1                  0   \n",
       "8289                 0                   1                  0   \n",
       "8290                 0                   0                  0   \n",
       "8291                 0                   0                  0   \n",
       "8292                 0                   0                  0   \n",
       "\n",
       "      Education_Doctor  Education_High School or Below  Education_Master  \\\n",
       "0                    0                               0                 0   \n",
       "1                    0                               0                 0   \n",
       "2                    0                               0                 0   \n",
       "3                    0                               0                 0   \n",
       "4                    0                               0                 0   \n",
       "5                    0                               0                 0   \n",
       "6                    0                               0                 0   \n",
       "7                    0                               0                 1   \n",
       "8                    0                               0                 0   \n",
       "9                    0                               0                 0   \n",
       "10                   0                               0                 0   \n",
       "11                   0                               0                 0   \n",
       "12                   0                               0                 1   \n",
       "13                   0                               1                 0   \n",
       "14                   0                               0                 0   \n",
       "15                   0                               0                 0   \n",
       "16                   0                               1                 0   \n",
       "17                   0                               0                 0   \n",
       "18                   0                               0                 0   \n",
       "19                   0                               1                 0   \n",
       "20                   0                               1                 0   \n",
       "21                   0                               0                 0   \n",
       "22                   0                               0                 0   \n",
       "23                   0                               0                 0   \n",
       "24                   0                               0                 0   \n",
       "25                   0                               0                 0   \n",
       "26                   0                               0                 0   \n",
       "27                   0                               0                 1   \n",
       "28                   0                               0                 0   \n",
       "29                   0                               0                 1   \n",
       "...                ...                             ...               ...   \n",
       "8263                 0                               0                 0   \n",
       "8264                 0                               0                 0   \n",
       "8265                 0                               1                 0   \n",
       "8266                 0                               0                 1   \n",
       "8267                 0                               0                 0   \n",
       "8268                 0                               1                 0   \n",
       "8269                 0                               1                 0   \n",
       "8270                 0                               0                 0   \n",
       "8271                 0                               0                 0   \n",
       "8272                 0                               0                 1   \n",
       "8273                 0                               0                 0   \n",
       "8274                 0                               0                 0   \n",
       "8275                 0                               0                 0   \n",
       "8276                 0                               1                 0   \n",
       "8277                 0                               0                 0   \n",
       "8278                 0                               0                 0   \n",
       "8279                 0                               0                 0   \n",
       "8280                 0                               0                 0   \n",
       "8281                 0                               0                 0   \n",
       "8282                 0                               0                 1   \n",
       "8283                 0                               1                 0   \n",
       "8284                 0                               1                 0   \n",
       "8285                 0                               0                 0   \n",
       "8286                 0                               0                 0   \n",
       "8287                 0                               1                 0   \n",
       "8288                 0                               0                 0   \n",
       "8289                 0                               0                 0   \n",
       "8290                 0                               1                 0   \n",
       "8291                 0                               1                 0   \n",
       "8292                 0                               1                 0   \n",
       "\n",
       "      EmploymentStatus_Disabled  EmploymentStatus_Employed  \\\n",
       "0                             0                          1   \n",
       "1                             0                          0   \n",
       "2                             0                          1   \n",
       "3                             0                          0   \n",
       "4                             0                          1   \n",
       "5                             0                          1   \n",
       "6                             0                          1   \n",
       "7                             0                          0   \n",
       "8                             0                          0   \n",
       "9                             0                          1   \n",
       "10                            0                          0   \n",
       "11                            0                          0   \n",
       "12                            0                          1   \n",
       "13                            0                          1   \n",
       "14                            0                          1   \n",
       "15                            0                          1   \n",
       "16                            0                          0   \n",
       "17                            0                          0   \n",
       "18                            0                          1   \n",
       "19                            0                          1   \n",
       "20                            0                          1   \n",
       "21                            1                          0   \n",
       "22                            0                          0   \n",
       "23                            0                          0   \n",
       "24                            1                          0   \n",
       "25                            0                          1   \n",
       "26                            0                          0   \n",
       "27                            1                          0   \n",
       "28                            0                          1   \n",
       "29                            0                          1   \n",
       "...                         ...                        ...   \n",
       "8263                          0                          0   \n",
       "8264                          0                          0   \n",
       "8265                          1                          0   \n",
       "8266                          0                          1   \n",
       "8267                          0                          1   \n",
       "8268                          0                          1   \n",
       "8269                          0                          1   \n",
       "8270                          0                          1   \n",
       "8271                          0                          1   \n",
       "8272                          0                          1   \n",
       "8273                          0                          1   \n",
       "8274                          0                          1   \n",
       "8275                          0                          0   \n",
       "8276                          0                          0   \n",
       "8277                          0                          1   \n",
       "8278                          0                          1   \n",
       "8279                          0                          0   \n",
       "8280                          0                          1   \n",
       "8281                          0                          0   \n",
       "8282                          0                          1   \n",
       "8283                          0                          0   \n",
       "8284                          1                          0   \n",
       "8285                          0                          1   \n",
       "8286                          0                          1   \n",
       "8287                          0                          0   \n",
       "8288                          0                          1   \n",
       "8289                          0                          1   \n",
       "8290                          0                          0   \n",
       "8291                          0                          1   \n",
       "8292                          0                          0   \n",
       "\n",
       "      EmploymentStatus_Medical Leave  EmploymentStatus_Retired  \\\n",
       "0                                  0                         0   \n",
       "1                                  0                         0   \n",
       "2                                  0                         0   \n",
       "3                                  0                         0   \n",
       "4                                  0                         0   \n",
       "5                                  0                         0   \n",
       "6                                  0                         0   \n",
       "7                                  0                         0   \n",
       "8                                  1                         0   \n",
       "9                                  0                         0   \n",
       "10                                 0                         0   \n",
       "11                                 0                         0   \n",
       "12                                 0                         0   \n",
       "13                                 0                         0   \n",
       "14                                 0                         0   \n",
       "15                                 0                         0   \n",
       "16                                 1                         0   \n",
       "17                                 1                         0   \n",
       "18                                 0                         0   \n",
       "19                                 0                         0   \n",
       "20                                 0                         0   \n",
       "21                                 0                         0   \n",
       "22                                 1                         0   \n",
       "23                                 0                         0   \n",
       "24                                 0                         0   \n",
       "25                                 0                         0   \n",
       "26                                 0                         0   \n",
       "27                                 0                         0   \n",
       "28                                 0                         0   \n",
       "29                                 0                         0   \n",
       "...                              ...                       ...   \n",
       "8263                               1                         0   \n",
       "8264                               0                         0   \n",
       "8265                               0                         0   \n",
       "8266                               0                         0   \n",
       "8267                               0                         0   \n",
       "8268                               0                         0   \n",
       "8269                               0                         0   \n",
       "8270                               0                         0   \n",
       "8271                               0                         0   \n",
       "8272                               0                         0   \n",
       "8273                               0                         0   \n",
       "8274                               0                         0   \n",
       "8275                               0                         0   \n",
       "8276                               0                         0   \n",
       "8277                               0                         0   \n",
       "8278                               0                         0   \n",
       "8279                               0                         0   \n",
       "8280                               0                         0   \n",
       "8281                               0                         0   \n",
       "8282                               0                         0   \n",
       "8283                               0                         0   \n",
       "8284                               0                         0   \n",
       "8285                               0                         0   \n",
       "8286                               0                         0   \n",
       "8287                               0                         0   \n",
       "8288                               0                         0   \n",
       "8289                               0                         0   \n",
       "8290                               0                         0   \n",
       "8291                               0                         0   \n",
       "8292                               0                         0   \n",
       "\n",
       "      EmploymentStatus_Unemployed  Gender_F  Gender_M  Location Code_Rur  \\\n",
       "0                               0         1         0                  0   \n",
       "1                               1         1         0                  0   \n",
       "2                               0         1         0                  0   \n",
       "3                               1         0         1                  0   \n",
       "4                               0         0         1                  1   \n",
       "5                               0         1         0                  1   \n",
       "6                               0         1         0                  0   \n",
       "7                               1         0         1                  0   \n",
       "8                               0         0         1                  0   \n",
       "9                               0         1         0                  0   \n",
       "10                              1         0         1                  0   \n",
       "11                              1         1         0                  0   \n",
       "12                              0         0         1                  0   \n",
       "13                              0         0         1                  0   \n",
       "14                              0         0         1                  0   \n",
       "15                              0         1         0                  1   \n",
       "16                              0         0         1                  0   \n",
       "17                              0         0         1                  0   \n",
       "18                              0         0         1                  0   \n",
       "19                              0         1         0                  0   \n",
       "20                              0         0         1                  0   \n",
       "21                              0         1         0                  0   \n",
       "22                              0         0         1                  0   \n",
       "23                              1         1         0                  0   \n",
       "24                              0         1         0                  0   \n",
       "25                              0         0         1                  0   \n",
       "26                              1         1         0                  0   \n",
       "27                              0         1         0                  0   \n",
       "28                              0         1         0                  0   \n",
       "29                              0         1         0                  0   \n",
       "...                           ...       ...       ...                ...   \n",
       "8263                            0         1         0                  0   \n",
       "8264                            1         0         1                  0   \n",
       "8265                            0         1         0                  0   \n",
       "8266                            0         1         0                  0   \n",
       "8267                            0         0         1                  0   \n",
       "8268                            0         0         1                  0   \n",
       "8269                            0         1         0                  0   \n",
       "8270                            0         1         0                  0   \n",
       "8271                            0         0         1                  0   \n",
       "8272                            0         1         0                  1   \n",
       "8273                            0         0         1                  1   \n",
       "8274                            0         0         1                  0   \n",
       "8275                            1         0         1                  0   \n",
       "8276                            1         0         1                  0   \n",
       "8277                            0         1         0                  0   \n",
       "8278                            0         0         1                  0   \n",
       "8279                            1         0         1                  0   \n",
       "8280                            0         1         0                  1   \n",
       "8281                            1         0         1                  0   \n",
       "8282                            0         0         1                  0   \n",
       "8283                            1         1         0                  0   \n",
       "8284                            0         1         0                  0   \n",
       "8285                            0         0         1                  0   \n",
       "8286                            0         0         1                  0   \n",
       "8287                            1         0         1                  0   \n",
       "8288                            0         0         1                  0   \n",
       "8289                            0         1         0                  0   \n",
       "8290                            1         0         1                  0   \n",
       "8291                            0         0         1                  0   \n",
       "8292                            1         0         1                  0   \n",
       "\n",
       "      Location Code_Sub  Location Code_Urb  Marital Status_Div  \\\n",
       "0                     1                  0                   0   \n",
       "1                     1                  0                   0   \n",
       "2                     1                  0                   0   \n",
       "3                     1                  0                   0   \n",
       "4                     0                  0                   0   \n",
       "5                     0                  0                   0   \n",
       "6                     1                  0                   0   \n",
       "7                     0                  1                   0   \n",
       "8                     1                  0                   1   \n",
       "9                     0                  1                   0   \n",
       "10                    1                  0                   0   \n",
       "11                    1                  0                   0   \n",
       "12                    0                  1                   0   \n",
       "13                    1                  0                   0   \n",
       "14                    0                  1                   0   \n",
       "15                    0                  0                   0   \n",
       "16                    1                  0                   0   \n",
       "17                    1                  0                   0   \n",
       "18                    0                  1                   0   \n",
       "19                    1                  0                   0   \n",
       "20                    1                  0                   0   \n",
       "21                    1                  0                   1   \n",
       "22                    1                  0                   1   \n",
       "23                    1                  0                   0   \n",
       "24                    1                  0                   0   \n",
       "25                    1                  0                   0   \n",
       "26                    1                  0                   0   \n",
       "27                    0                  1                   0   \n",
       "28                    1                  0                   0   \n",
       "29                    1                  0                   0   \n",
       "...                 ...                ...                 ...   \n",
       "8263                  1                  0                   0   \n",
       "8264                  1                  0                   0   \n",
       "8265                  1                  0                   1   \n",
       "8266                  1                  0                   1   \n",
       "8267                  1                  0                   1   \n",
       "8268                  1                  0                   1   \n",
       "8269                  1                  0                   0   \n",
       "8270                  0                  1                   0   \n",
       "8271                  1                  0                   1   \n",
       "8272                  0                  0                   0   \n",
       "8273                  0                  0                   0   \n",
       "8274                  0                  1                   0   \n",
       "8275                  1                  0                   0   \n",
       "8276                  1                  0                   0   \n",
       "8277                  0                  1                   1   \n",
       "8278                  1                  0                   0   \n",
       "8279                  1                  0                   0   \n",
       "8280                  0                  0                   0   \n",
       "8281                  1                  0                   0   \n",
       "8282                  1                  0                   1   \n",
       "8283                  1                  0                   0   \n",
       "8284                  1                  0                   0   \n",
       "8285                  1                  0                   0   \n",
       "8286                  1                  0                   1   \n",
       "8287                  1                  0                   1   \n",
       "8288                  1                  0                   0   \n",
       "8289                  0                  1                   0   \n",
       "8290                  1                  0                   0   \n",
       "8291                  0                  1                   0   \n",
       "8292                  1                  0                   0   \n",
       "\n",
       "      Marital Status_Mar  Marital Status_Sin  Policy Type_Corporate Auto  \\\n",
       "0                      1                   0                           1   \n",
       "1                      0                   1                           0   \n",
       "2                      1                   0                           0   \n",
       "3                      1                   0                           1   \n",
       "4                      0                   1                           0   \n",
       "5                      1                   0                           0   \n",
       "6                      1                   0                           1   \n",
       "7                      0                   1                           1   \n",
       "8                      0                   0                           1   \n",
       "9                      1                   0                           0   \n",
       "10                     0                   1                           0   \n",
       "11                     1                   0                           0   \n",
       "12                     1                   0                           1   \n",
       "13                     1                   0                           1   \n",
       "14                     0                   1                           1   \n",
       "15                     1                   0                           1   \n",
       "16                     1                   0                           0   \n",
       "17                     1                   0                           0   \n",
       "18                     1                   0                           0   \n",
       "19                     1                   0                           1   \n",
       "20                     0                   1                           0   \n",
       "21                     0                   0                           0   \n",
       "22                     0                   0                           0   \n",
       "23                     0                   1                           1   \n",
       "24                     1                   0                           1   \n",
       "25                     1                   0                           0   \n",
       "26                     0                   1                           0   \n",
       "27                     1                   0                           1   \n",
       "28                     0                   1                           0   \n",
       "29                     1                   0                           0   \n",
       "...                  ...                 ...                         ...   \n",
       "8263                   1                   0                           0   \n",
       "8264                   0                   1                           1   \n",
       "8265                   0                   0                           0   \n",
       "8266                   0                   0                           0   \n",
       "8267                   0                   0                           1   \n",
       "8268                   0                   0                           0   \n",
       "8269                   0                   1                           0   \n",
       "8270                   1                   0                           1   \n",
       "8271                   0                   0                           1   \n",
       "8272                   0                   1                           0   \n",
       "8273                   1                   0                           0   \n",
       "8274                   1                   0                           0   \n",
       "8275                   1                   0                           0   \n",
       "8276                   0                   1                           1   \n",
       "8277                   0                   0                           0   \n",
       "8278                   0                   1                           0   \n",
       "8279                   1                   0                           1   \n",
       "8280                   1                   0                           0   \n",
       "8281                   0                   1                           0   \n",
       "8282                   0                   0                           0   \n",
       "8283                   0                   1                           0   \n",
       "8284                   0                   1                           1   \n",
       "8285                   1                   0                           0   \n",
       "8286                   0                   0                           0   \n",
       "8287                   0                   0                           0   \n",
       "8288                   1                   0                           0   \n",
       "8289                   0                   1                           0   \n",
       "8290                   0                   1                           0   \n",
       "8291                   1                   0                           1   \n",
       "8292                   0                   1                           0   \n",
       "\n",
       "      Policy Type_Personal Auto  Policy Type_Special Auto  \\\n",
       "0                             0                         0   \n",
       "1                             1                         0   \n",
       "2                             1                         0   \n",
       "3                             0                         0   \n",
       "4                             1                         0   \n",
       "5                             1                         0   \n",
       "6                             0                         0   \n",
       "7                             0                         0   \n",
       "8                             0                         0   \n",
       "9                             0                         1   \n",
       "10                            1                         0   \n",
       "11                            1                         0   \n",
       "12                            0                         0   \n",
       "13                            0                         0   \n",
       "14                            0                         0   \n",
       "15                            0                         0   \n",
       "16                            1                         0   \n",
       "17                            1                         0   \n",
       "18                            1                         0   \n",
       "19                            0                         0   \n",
       "20                            1                         0   \n",
       "21                            1                         0   \n",
       "22                            1                         0   \n",
       "23                            0                         0   \n",
       "24                            0                         0   \n",
       "25                            1                         0   \n",
       "26                            1                         0   \n",
       "27                            0                         0   \n",
       "28                            1                         0   \n",
       "29                            1                         0   \n",
       "...                         ...                       ...   \n",
       "8263                          1                         0   \n",
       "8264                          0                         0   \n",
       "8265                          1                         0   \n",
       "8266                          1                         0   \n",
       "8267                          0                         0   \n",
       "8268                          1                         0   \n",
       "8269                          1                         0   \n",
       "8270                          0                         0   \n",
       "8271                          0                         0   \n",
       "8272                          1                         0   \n",
       "8273                          1                         0   \n",
       "8274                          0                         1   \n",
       "8275                          1                         0   \n",
       "8276                          0                         0   \n",
       "8277                          1                         0   \n",
       "8278                          1                         0   \n",
       "8279                          0                         0   \n",
       "8280                          1                         0   \n",
       "8281                          1                         0   \n",
       "8282                          1                         0   \n",
       "8283                          1                         0   \n",
       "8284                          0                         0   \n",
       "8285                          1                         0   \n",
       "8286                          1                         0   \n",
       "8287                          1                         0   \n",
       "8288                          1                         0   \n",
       "8289                          1                         0   \n",
       "8290                          1                         0   \n",
       "8291                          0                         0   \n",
       "8292                          1                         0   \n",
       "\n",
       "      Sales Channel_Agent  Sales Channel_Branch  Sales Channel_Call Center  \\\n",
       "0                       1                     0                          0   \n",
       "1                       1                     0                          0   \n",
       "2                       1                     0                          0   \n",
       "3                       0                     0                          1   \n",
       "4                       1                     0                          0   \n",
       "5                       0                     0                          0   \n",
       "6                       1                     0                          0   \n",
       "7                       1                     0                          0   \n",
       "8                       1                     0                          0   \n",
       "9                       0                     1                          0   \n",
       "10                      1                     0                          0   \n",
       "11                      1                     0                          0   \n",
       "12                      1                     0                          0   \n",
       "13                      0                     1                          0   \n",
       "14                      0                     0                          1   \n",
       "15                      0                     1                          0   \n",
       "16                      0                     0                          1   \n",
       "17                      0                     0                          1   \n",
       "18                      0                     1                          0   \n",
       "19                      0                     0                          1   \n",
       "20                      0                     1                          0   \n",
       "21                      0                     0                          1   \n",
       "22                      1                     0                          0   \n",
       "23                      0                     1                          0   \n",
       "24                      0                     1                          0   \n",
       "25                      0                     0                          1   \n",
       "26                      1                     0                          0   \n",
       "27                      0                     1                          0   \n",
       "28                      0                     0                          1   \n",
       "29                      0                     1                          0   \n",
       "...                   ...                   ...                        ...   \n",
       "8263                    0                     1                          0   \n",
       "8264                    1                     0                          0   \n",
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       "8280                    0                     1                          0   \n",
       "8281                    0                     0                          1   \n",
       "8282                    0                     0                          1   \n",
       "8283                    0                     1                          0   \n",
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       "8287                    0                     0                          1   \n",
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       "8290                    0                     0                          0   \n",
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       "8292                    0                     0                          1   \n",
       "\n",
       "      Sales Channel_Web  \n",
       "0                     0  \n",
       "1                     0  \n",
       "2                     0  \n",
       "3                     0  \n",
       "4                     0  \n",
       "5                     1  \n",
       "6                     0  \n",
       "7                     0  \n",
       "8                     0  \n",
       "9                     0  \n",
       "10                    0  \n",
       "11                    0  \n",
       "12                    0  \n",
       "13                    0  \n",
       "14                    0  \n",
       "15                    0  \n",
       "16                    0  \n",
       "17                    0  \n",
       "18                    0  \n",
       "19                    0  \n",
       "20                    0  \n",
       "21                    0  \n",
       "22                    0  \n",
       "23                    0  \n",
       "24                    0  \n",
       "25                    0  \n",
       "26                    0  \n",
       "27                    0  \n",
       "28                    0  \n",
       "29                    0  \n",
       "...                 ...  \n",
       "8263                  0  \n",
       "8264                  0  \n",
       "8265                  0  \n",
       "8266                  0  \n",
       "8267                  0  \n",
       "8268                  0  \n",
       "8269                  0  \n",
       "8270                  0  \n",
       "8271                  0  \n",
       "8272                  1  \n",
       "8273                  0  \n",
       "8274                  1  \n",
       "8275                  0  \n",
       "8276                  0  \n",
       "8277                  0  \n",
       "8278                  0  \n",
       "8279                  0  \n",
       "8280                  0  \n",
       "8281                  0  \n",
       "8282                  0  \n",
       "8283                  0  \n",
       "8284                  0  \n",
       "8285                  0  \n",
       "8286                  0  \n",
       "8287                  0  \n",
       "8288                  0  \n",
       "8289                  0  \n",
       "8290                  1  \n",
       "8291                  0  \n",
       "8292                  0  \n",
       "\n",
       "[8293 rows x 42 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.set_option('display.max_columns', 50)\n",
    "display(data_dummies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y = data_dummies.loc[:, 'Response_Yes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data_dummies.drop('Response_No', axis=1, inplace=True)\n",
    "data_dummies.drop('Response_Yes', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "      <th>Income</th>\n",
       "      <th>Monthly Premium Auto</th>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8256.297800</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7216.100311</td>\n",
       "      <td>0</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>68.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>24127.504020</td>\n",
       "      <td>14072</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7388.178085</td>\n",
       "      <td>28812</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4738.992022</td>\n",
       "      <td>0</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>5.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>8197.197078</td>\n",
       "      <td>0</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>87.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>8798.797003</td>\n",
       "      <td>77026</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>8819.018934</td>\n",
       "      <td>99845</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>25.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.965259</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5384.431665</td>\n",
       "      <td>83689</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7463.139377</td>\n",
       "      <td>24599</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>50.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.965259</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2566.867823</td>\n",
       "      <td>25049</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>7.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>3945.241604</td>\n",
       "      <td>28855</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>59.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>5710.333115</td>\n",
       "      <td>51148</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.389626</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>8162.617053</td>\n",
       "      <td>66140</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2872.051273</td>\n",
       "      <td>57749</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>3041.791561</td>\n",
       "      <td>13789</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>49.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>24127.504020</td>\n",
       "      <td>14072</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2450.190996</td>\n",
       "      <td>0</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>44.00000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2392.107890</td>\n",
       "      <td>17870</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>91.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>5802.065978</td>\n",
       "      <td>97541</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>3946.372085</td>\n",
       "      <td>0</td>\n",
       "      <td>93.196573</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>47.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>5346.916576</td>\n",
       "      <td>10511</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>48.14515</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>12902.560140</td>\n",
       "      <td>86584</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>54.00000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.965259</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>3235.360468</td>\n",
       "      <td>75690</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>15.077925</td>\n",
       "      <td>44.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8263</th>\n",
       "      <td>11638.899470</td>\n",
       "      <td>25370</td>\n",
       "      <td>102.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>77.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8264</th>\n",
       "      <td>7376.795372</td>\n",
       "      <td>0</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>85.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8265</th>\n",
       "      <td>7892.088107</td>\n",
       "      <td>28672</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>34.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8266</th>\n",
       "      <td>19160.989940</td>\n",
       "      <td>22705</td>\n",
       "      <td>239.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>59.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8267</th>\n",
       "      <td>5548.031892</td>\n",
       "      <td>67798</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>78.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8268</th>\n",
       "      <td>8319.529200</td>\n",
       "      <td>61367</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>85.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8269</th>\n",
       "      <td>13770.976180</td>\n",
       "      <td>59207</td>\n",
       "      <td>116.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8270</th>\n",
       "      <td>5225.253777</td>\n",
       "      <td>67423</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8271</th>\n",
       "      <td>16979.797570</td>\n",
       "      <td>35095</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>56.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8272</th>\n",
       "      <td>7485.356469</td>\n",
       "      <td>26380</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>70.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8273</th>\n",
       "      <td>2639.644171</td>\n",
       "      <td>88731</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>72.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8274</th>\n",
       "      <td>8085.448545</td>\n",
       "      <td>61409</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>80.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8275</th>\n",
       "      <td>12316.796980</td>\n",
       "      <td>0</td>\n",
       "      <td>167.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>40.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8276</th>\n",
       "      <td>5568.947534</td>\n",
       "      <td>0</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>53.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8277</th>\n",
       "      <td>3571.828310</td>\n",
       "      <td>74931</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>16.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8278</th>\n",
       "      <td>3350.244285</td>\n",
       "      <td>74770</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8279</th>\n",
       "      <td>2716.190293</td>\n",
       "      <td>0</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>81.00000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8280</th>\n",
       "      <td>38887.903400</td>\n",
       "      <td>44299</td>\n",
       "      <td>107.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>73.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8281</th>\n",
       "      <td>2272.447229</td>\n",
       "      <td>0</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>10.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8282</th>\n",
       "      <td>2849.252467</td>\n",
       "      <td>63326</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>34.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8283</th>\n",
       "      <td>5328.320299</td>\n",
       "      <td>0</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>42.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8284</th>\n",
       "      <td>4679.977728</td>\n",
       "      <td>21720</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>7.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8285</th>\n",
       "      <td>5345.201117</td>\n",
       "      <td>55571</td>\n",
       "      <td>135.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>46.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8286</th>\n",
       "      <td>2437.084486</td>\n",
       "      <td>34759</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>84.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8287</th>\n",
       "      <td>4637.544647</td>\n",
       "      <td>0</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>81.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8288</th>\n",
       "      <td>8804.584902</td>\n",
       "      <td>38638</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>84.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8289</th>\n",
       "      <td>2438.689804</td>\n",
       "      <td>80927</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>8.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8290</th>\n",
       "      <td>4736.347990</td>\n",
       "      <td>0</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8291</th>\n",
       "      <td>5608.155723</td>\n",
       "      <td>81914</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>33.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8292</th>\n",
       "      <td>6465.223746</td>\n",
       "      <td>0</td>\n",
       "      <td>92.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>24.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8293 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Customer Lifetime Value  Income  Monthly Premium Auto  \\\n",
       "0                 2763.519279   56274             93.196573   \n",
       "1                 6979.535903       0             93.196573   \n",
       "2                12887.431650   48767            108.000000   \n",
       "3                 7645.861827       0            106.000000   \n",
       "4                 2813.692575   43836             73.000000   \n",
       "5                 8256.297800   62902             69.000000   \n",
       "6                 5380.898636   55350             67.000000   \n",
       "7                 7216.100311       0            101.000000   \n",
       "8                24127.504020   14072             71.000000   \n",
       "9                 7388.178085   28812             93.000000   \n",
       "10                4738.992022       0             67.000000   \n",
       "11                8197.197078       0            110.000000   \n",
       "12                8798.797003   77026            110.000000   \n",
       "13                8819.018934   99845            110.000000   \n",
       "14                5384.431665   83689             70.000000   \n",
       "15                7463.139377   24599             64.000000   \n",
       "16                2566.867823   25049             67.000000   \n",
       "17                3945.241604   28855            101.000000   \n",
       "18                5710.333115   51148             93.196573   \n",
       "19                8162.617053   66140            101.000000   \n",
       "20                2872.051273   57749             93.196573   \n",
       "21                3041.791561   13789             93.196573   \n",
       "22               24127.504020   14072             71.000000   \n",
       "23                2450.190996       0             73.000000   \n",
       "24                2392.107890   17870             61.000000   \n",
       "25                5802.065978   97541             72.000000   \n",
       "26                3946.372085       0             93.196573   \n",
       "27                5346.916576   10511            139.000000   \n",
       "28               12902.560140   86584            111.000000   \n",
       "29                3235.360468   75690             80.000000   \n",
       "...                       ...     ...                   ...   \n",
       "8263             11638.899470   25370            102.000000   \n",
       "8264              7376.795372       0            105.000000   \n",
       "8265              7892.088107   28672             71.000000   \n",
       "8266             19160.989940   22705            239.000000   \n",
       "8267              5548.031892   67798             69.000000   \n",
       "8268              8319.529200   61367             70.000000   \n",
       "8269             13770.976180   59207            116.000000   \n",
       "8270              5225.253777   67423             65.000000   \n",
       "8271             16979.797570   35095             73.000000   \n",
       "8272              7485.356469   26380             96.000000   \n",
       "8273              2639.644171   88731             66.000000   \n",
       "8274              8085.448545   61409             68.000000   \n",
       "8275             12316.796980       0            167.000000   \n",
       "8276              5568.947534       0             79.000000   \n",
       "8277              3571.828310   74931             89.000000   \n",
       "8278              3350.244285   74770             86.000000   \n",
       "8279              2716.190293       0             95.000000   \n",
       "8280             38887.903400   44299            107.000000   \n",
       "8281              2272.447229       0             71.000000   \n",
       "8282              2849.252467   63326             72.000000   \n",
       "8283              5328.320299       0             73.000000   \n",
       "8284              4679.977728   21720            128.000000   \n",
       "8285              5345.201117   55571            135.000000   \n",
       "8286              2437.084486   34759             61.000000   \n",
       "8287              4637.544647       0             68.000000   \n",
       "8288              8804.584902   38638             74.000000   \n",
       "8289              2438.689804   80927             62.000000   \n",
       "8290              4736.347990       0             65.000000   \n",
       "8291              5608.155723   81914             70.000000   \n",
       "8292              6465.223746       0             92.000000   \n",
       "\n",
       "      Months Since Last Claim  Months Since Policy Inception  \\\n",
       "0                   32.000000                        5.00000   \n",
       "1                   13.000000                       42.00000   \n",
       "2                   15.077925                       38.00000   \n",
       "3                   18.000000                       65.00000   \n",
       "4                   12.000000                       44.00000   \n",
       "5                   14.000000                       94.00000   \n",
       "6                    0.000000                       13.00000   \n",
       "7                    0.000000                       68.00000   \n",
       "8                   13.000000                        3.00000   \n",
       "9                   17.000000                       48.14515   \n",
       "10                  15.077925                        5.00000   \n",
       "11                  27.000000                       87.00000   \n",
       "12                   9.000000                       48.14515   \n",
       "13                  23.000000                       25.00000   \n",
       "14                  21.000000                       48.14515   \n",
       "15                  12.000000                       50.00000   \n",
       "16                  14.000000                        7.00000   \n",
       "17                  12.000000                       59.00000   \n",
       "18                   9.000000                        1.00000   \n",
       "19                  11.000000                       21.00000   \n",
       "20                  31.000000                       21.00000   \n",
       "21                   8.000000                       49.00000   \n",
       "22                  13.000000                        3.00000   \n",
       "23                   4.000000                       44.00000   \n",
       "24                  30.000000                       91.00000   \n",
       "25                  22.000000                        1.00000   \n",
       "26                  15.000000                       47.00000   \n",
       "27                  33.000000                       48.14515   \n",
       "28                  33.000000                       54.00000   \n",
       "29                  15.077925                       44.00000   \n",
       "...                       ...                            ...   \n",
       "8263                10.000000                       77.00000   \n",
       "8264                31.000000                       85.00000   \n",
       "8265                14.000000                       34.00000   \n",
       "8266                19.000000                       59.00000   \n",
       "8267                 1.000000                       78.00000   \n",
       "8268                 7.000000                       85.00000   \n",
       "8269                23.000000                       21.00000   \n",
       "8270                24.000000                        0.00000   \n",
       "8271                25.000000                       56.00000   \n",
       "8272                29.000000                       70.00000   \n",
       "8273                10.000000                       72.00000   \n",
       "8274                30.000000                       80.00000   \n",
       "8275                30.000000                       40.00000   \n",
       "8276                21.000000                       53.00000   \n",
       "8277                13.000000                       16.00000   \n",
       "8278                23.000000                       10.00000   \n",
       "8279                14.000000                       81.00000   \n",
       "8280                 0.000000                       73.00000   \n",
       "8281                22.000000                       10.00000   \n",
       "8282                 2.000000                       34.00000   \n",
       "8283                12.000000                       42.00000   \n",
       "8284                 5.000000                        7.00000   \n",
       "8285                 4.000000                       46.00000   \n",
       "8286                30.000000                       84.00000   \n",
       "8287                18.000000                       81.00000   \n",
       "8288                 5.000000                       84.00000   \n",
       "8289                25.000000                        8.00000   \n",
       "8290                33.000000                        1.00000   \n",
       "8291                 6.000000                       33.00000   \n",
       "8292                 9.000000                       24.00000   \n",
       "\n",
       "      Number of Open Complaints  Number of Policies  State_Arizona  \\\n",
       "0                      0.389626            1.000000              0   \n",
       "1                      0.389626            8.000000              1   \n",
       "2                      0.000000            2.000000              0   \n",
       "3                      0.000000            7.000000              0   \n",
       "4                      0.000000            1.000000              0   \n",
       "5                      0.000000            2.000000              0   \n",
       "6                      0.000000            9.000000              0   \n",
       "7                      0.000000            4.000000              1   \n",
       "8                      0.000000            2.000000              0   \n",
       "9                      0.000000            8.000000              0   \n",
       "10                     0.000000            3.000000              0   \n",
       "11                     0.000000            3.000000              0   \n",
       "12                     2.000000            3.000000              0   \n",
       "13                     1.000000            2.965259              1   \n",
       "14                     2.000000            8.000000              0   \n",
       "15                     1.000000            2.965259              0   \n",
       "16                     0.000000            1.000000              0   \n",
       "17                     0.000000            1.000000              0   \n",
       "18                     0.389626            7.000000              0   \n",
       "19                     0.000000            3.000000              0   \n",
       "20                     0.000000            1.000000              0   \n",
       "21                     0.000000            1.000000              0   \n",
       "22                     0.000000            2.000000              1   \n",
       "23                     3.000000            1.000000              0   \n",
       "24                     0.000000            1.000000              0   \n",
       "25                     0.000000            3.000000              0   \n",
       "26                     0.000000            1.000000              0   \n",
       "27                     0.000000            1.000000              0   \n",
       "28                     2.000000            2.965259              1   \n",
       "29                     1.000000            1.000000              0   \n",
       "...                         ...                 ...            ...   \n",
       "8263                   0.000000            2.000000              0   \n",
       "8264                   0.000000            5.000000              0   \n",
       "8265                   0.000000            2.000000              0   \n",
       "8266                   0.000000            7.000000              0   \n",
       "8267                   0.000000            9.000000              0   \n",
       "8268                   0.000000            2.000000              1   \n",
       "8269                   0.000000            2.000000              1   \n",
       "8270                   0.000000            9.000000              0   \n",
       "8271                   0.000000            2.000000              0   \n",
       "8272                   0.000000            4.000000              0   \n",
       "8273                   0.000000            1.000000              0   \n",
       "8274                   0.000000            2.000000              0   \n",
       "8275                   0.000000            5.000000              0   \n",
       "8276                   1.000000            7.000000              0   \n",
       "8277                   0.000000            1.000000              0   \n",
       "8278                   0.000000            1.000000              0   \n",
       "8279                   5.000000            1.000000              1   \n",
       "8280                   0.000000            2.000000              0   \n",
       "8281                   1.000000            1.000000              1   \n",
       "8282                   0.000000            1.000000              0   \n",
       "8283                   0.000000            7.000000              0   \n",
       "8284                   0.000000            1.000000              0   \n",
       "8285                   0.000000            1.000000              0   \n",
       "8286                   0.000000            1.000000              0   \n",
       "8287                   0.000000            3.000000              1   \n",
       "8288                   0.000000            2.000000              0   \n",
       "8289                   0.000000            1.000000              0   \n",
       "8290                   0.000000            3.000000              0   \n",
       "8291                   0.000000            6.000000              1   \n",
       "8292                   0.000000            3.000000              0   \n",
       "\n",
       "      State_California  State_Nevada  State_Oregon  State_Washington  \\\n",
       "0                    0             0             0                 1   \n",
       "1                    0             0             0                 0   \n",
       "2                    0             1             0                 0   \n",
       "3                    1             0             0                 0   \n",
       "4                    0             0             0                 1   \n",
       "5                    0             0             1                 0   \n",
       "6                    0             0             1                 0   \n",
       "7                    0             0             0                 0   \n",
       "8                    0             0             1                 0   \n",
       "9                    0             0             1                 0   \n",
       "10                   1             0             0                 0   \n",
       "11                   1             0             0                 0   \n",
       "12                   1             0             0                 0   \n",
       "13                   0             0             0                 0   \n",
       "14                   1             0             0                 0   \n",
       "15                   0             0             1                 0   \n",
       "16                   0             1             0                 0   \n",
       "17                   1             0             0                 0   \n",
       "18                   0             0             1                 0   \n",
       "19                   1             0             0                 0   \n",
       "20                   0             0             1                 0   \n",
       "21                   0             0             0                 1   \n",
       "22                   0             0             0                 0   \n",
       "23                   0             1             0                 0   \n",
       "24                   1             0             0                 0   \n",
       "25                   0             0             1                 0   \n",
       "26                   1             0             0                 0   \n",
       "27                   0             0             0                 1   \n",
       "28                   0             0             0                 0   \n",
       "29                   0             0             1                 0   \n",
       "...                ...           ...           ...               ...   \n",
       "8263                 1             0             0                 0   \n",
       "8264                 1             0             0                 0   \n",
       "8265                 1             0             0                 0   \n",
       "8266                 1             0             0                 0   \n",
       "8267                 0             0             0                 1   \n",
       "8268                 0             0             0                 0   \n",
       "8269                 0             0             0                 0   \n",
       "8270                 0             0             0                 1   \n",
       "8271                 1             0             0                 0   \n",
       "8272                 0             0             1                 0   \n",
       "8273                 0             0             1                 0   \n",
       "8274                 0             0             1                 0   \n",
       "8275                 1             0             0                 0   \n",
       "8276                 0             1             0                 0   \n",
       "8277                 1             0             0                 0   \n",
       "8278                 0             0             1                 0   \n",
       "8279                 0             0             0                 0   \n",
       "8280                 1             0             0                 0   \n",
       "8281                 0             0             0                 0   \n",
       "8282                 1             0             0                 0   \n",
       "8283                 0             0             1                 0   \n",
       "8284                 1             0             0                 0   \n",
       "8285                 0             0             1                 0   \n",
       "8286                 1             0             0                 0   \n",
       "8287                 0             0             0                 0   \n",
       "8288                 0             0             1                 0   \n",
       "8289                 1             0             0                 0   \n",
       "8290                 1             0             0                 0   \n",
       "8291                 0             0             0                 0   \n",
       "8292                 0             0             1                 0   \n",
       "\n",
       "      Coverage_Basic  Coverage_Extended  Coverage_Premium  Education_Bachelor  \\\n",
       "0                  1                  0                 0                   1   \n",
       "1                  0                  1                 0                   1   \n",
       "2                  0                  0                 1                   1   \n",
       "3                  1                  0                 0                   1   \n",
       "4                  1                  0                 0                   1   \n",
       "5                  1                  0                 0                   1   \n",
       "6                  1                  0                 0                   0   \n",
       "7                  0                  0                 1                   0   \n",
       "8                  1                  0                 0                   1   \n",
       "9                  0                  1                 0                   1   \n",
       "10                 1                  0                 0                   0   \n",
       "11                 1                  0                 0                   0   \n",
       "12                 0                  0                 1                   0   \n",
       "13                 1                  0                 0                   0   \n",
       "14                 1                  0                 0                   0   \n",
       "15                 1                  0                 0                   1   \n",
       "16                 1                  0                 0                   0   \n",
       "17                 1                  0                 0                   0   \n",
       "18                 1                  0                 0                   0   \n",
       "19                 0                  0                 1                   0   \n",
       "20                 1                  0                 0                   0   \n",
       "21                 0                  1                 0                   1   \n",
       "22                 1                  0                 0                   1   \n",
       "23                 1                  0                 0                   1   \n",
       "24                 1                  0                 0                   1   \n",
       "25                 1                  0                 0                   0   \n",
       "26                 0                  0                 1                   1   \n",
       "27                 0                  1                 0                   0   \n",
       "28                 0                  0                 1                   0   \n",
       "29                 0                  1                 0                   0   \n",
       "...              ...                ...               ...                 ...   \n",
       "8263               1                  0                 0                   0   \n",
       "8264               1                  0                 0                   1   \n",
       "8265               1                  0                 0                   0   \n",
       "8266               0                  1                 0                   0   \n",
       "8267               1                  0                 0                   1   \n",
       "8268               1                  0                 0                   0   \n",
       "8269               0                  0                 1                   0   \n",
       "8270               1                  0                 0                   0   \n",
       "8271               1                  0                 0                   1   \n",
       "8272               0                  1                 0                   0   \n",
       "8273               1                  0                 0                   0   \n",
       "8274               1                  0                 0                   1   \n",
       "8275               0                  0                 1                   1   \n",
       "8276               0                  1                 0                   0   \n",
       "8277               0                  1                 0                   1   \n",
       "8278               0                  1                 0                   0   \n",
       "8279               0                  1                 0                   1   \n",
       "8280               0                  0                 1                   1   \n",
       "8281               1                  0                 0                   0   \n",
       "8282               1                  0                 0                   0   \n",
       "8283               1                  0                 0                   0   \n",
       "8284               0                  1                 0                   0   \n",
       "8285               0                  1                 0                   0   \n",
       "8286               1                  0                 0                   0   \n",
       "8287               1                  0                 0                   0   \n",
       "8288               1                  0                 0                   1   \n",
       "8289               1                  0                 0                   1   \n",
       "8290               1                  0                 0                   0   \n",
       "8291               1                  0                 0                   0   \n",
       "8292               0                  1                 0                   0   \n",
       "\n",
       "      Education_College  Education_Doctor  Education_High School or Below  \\\n",
       "0                     0                 0                               0   \n",
       "1                     0                 0                               0   \n",
       "2                     0                 0                               0   \n",
       "3                     0                 0                               0   \n",
       "4                     0                 0                               0   \n",
       "5                     0                 0                               0   \n",
       "6                     1                 0                               0   \n",
       "7                     0                 0                               0   \n",
       "8                     0                 0                               0   \n",
       "9                     0                 0                               0   \n",
       "10                    1                 0                               0   \n",
       "11                    1                 0                               0   \n",
       "12                    0                 0                               0   \n",
       "13                    0                 0                               1   \n",
       "14                    1                 0                               0   \n",
       "15                    0                 0                               0   \n",
       "16                    0                 0                               1   \n",
       "17                    1                 0                               0   \n",
       "18                    1                 0                               0   \n",
       "19                    0                 0                               1   \n",
       "20                    0                 0                               1   \n",
       "21                    0                 0                               0   \n",
       "22                    0                 0                               0   \n",
       "23                    0                 0                               0   \n",
       "24                    0                 0                               0   \n",
       "25                    1                 0                               0   \n",
       "26                    0                 0                               0   \n",
       "27                    0                 0                               0   \n",
       "28                    1                 0                               0   \n",
       "29                    0                 0                               0   \n",
       "...                 ...               ...                             ...   \n",
       "8263                  1                 0                               0   \n",
       "8264                  0                 0                               0   \n",
       "8265                  0                 0                               1   \n",
       "8266                  0                 0                               0   \n",
       "8267                  0                 0                               0   \n",
       "8268                  0                 0                               1   \n",
       "8269                  0                 0                               1   \n",
       "8270                  1                 0                               0   \n",
       "8271                  0                 0                               0   \n",
       "8272                  0                 0                               0   \n",
       "8273                  1                 0                               0   \n",
       "8274                  0                 0                               0   \n",
       "8275                  0                 0                               0   \n",
       "8276                  0                 0                               1   \n",
       "8277                  0                 0                               0   \n",
       "8278                  1                 0                               0   \n",
       "8279                  0                 0                               0   \n",
       "8280                  0                 0                               0   \n",
       "8281                  1                 0                               0   \n",
       "8282                  0                 0                               0   \n",
       "8283                  0                 0                               1   \n",
       "8284                  0                 0                               1   \n",
       "8285                  1                 0                               0   \n",
       "8286                  1                 0                               0   \n",
       "8287                  0                 0                               1   \n",
       "8288                  0                 0                               0   \n",
       "8289                  0                 0                               0   \n",
       "8290                  0                 0                               1   \n",
       "8291                  0                 0                               1   \n",
       "8292                  0                 0                               1   \n",
       "\n",
       "      Education_Master  EmploymentStatus_Disabled  EmploymentStatus_Employed  \\\n",
       "0                    0                          0                          1   \n",
       "1                    0                          0                          0   \n",
       "2                    0                          0                          1   \n",
       "3                    0                          0                          0   \n",
       "4                    0                          0                          1   \n",
       "5                    0                          0                          1   \n",
       "6                    0                          0                          1   \n",
       "7                    1                          0                          0   \n",
       "8                    0                          0                          0   \n",
       "9                    0                          0                          1   \n",
       "10                   0                          0                          0   \n",
       "11                   0                          0                          0   \n",
       "12                   1                          0                          1   \n",
       "13                   0                          0                          1   \n",
       "14                   0                          0                          1   \n",
       "15                   0                          0                          1   \n",
       "16                   0                          0                          0   \n",
       "17                   0                          0                          0   \n",
       "18                   0                          0                          1   \n",
       "19                   0                          0                          1   \n",
       "20                   0                          0                          1   \n",
       "21                   0                          1                          0   \n",
       "22                   0                          0                          0   \n",
       "23                   0                          0                          0   \n",
       "24                   0                          1                          0   \n",
       "25                   0                          0                          1   \n",
       "26                   0                          0                          0   \n",
       "27                   1                          1                          0   \n",
       "28                   0                          0                          1   \n",
       "29                   1                          0                          1   \n",
       "...                ...                        ...                        ...   \n",
       "8263                 0                          0                          0   \n",
       "8264                 0                          0                          0   \n",
       "8265                 0                          1                          0   \n",
       "8266                 1                          0                          1   \n",
       "8267                 0                          0                          1   \n",
       "8268                 0                          0                          1   \n",
       "8269                 0                          0                          1   \n",
       "8270                 0                          0                          1   \n",
       "8271                 0                          0                          1   \n",
       "8272                 1                          0                          1   \n",
       "8273                 0                          0                          1   \n",
       "8274                 0                          0                          1   \n",
       "8275                 0                          0                          0   \n",
       "8276                 0                          0                          0   \n",
       "8277                 0                          0                          1   \n",
       "8278                 0                          0                          1   \n",
       "8279                 0                          0                          0   \n",
       "8280                 0                          0                          1   \n",
       "8281                 0                          0                          0   \n",
       "8282                 1                          0                          1   \n",
       "8283                 0                          0                          0   \n",
       "8284                 0                          1                          0   \n",
       "8285                 0                          0                          1   \n",
       "8286                 0                          0                          1   \n",
       "8287                 0                          0                          0   \n",
       "8288                 0                          0                          1   \n",
       "8289                 0                          0                          1   \n",
       "8290                 0                          0                          0   \n",
       "8291                 0                          0                          1   \n",
       "8292                 0                          0                          0   \n",
       "\n",
       "      EmploymentStatus_Medical Leave  EmploymentStatus_Retired  \\\n",
       "0                                  0                         0   \n",
       "1                                  0                         0   \n",
       "2                                  0                         0   \n",
       "3                                  0                         0   \n",
       "4                                  0                         0   \n",
       "5                                  0                         0   \n",
       "6                                  0                         0   \n",
       "7                                  0                         0   \n",
       "8                                  1                         0   \n",
       "9                                  0                         0   \n",
       "10                                 0                         0   \n",
       "11                                 0                         0   \n",
       "12                                 0                         0   \n",
       "13                                 0                         0   \n",
       "14                                 0                         0   \n",
       "15                                 0                         0   \n",
       "16                                 1                         0   \n",
       "17                                 1                         0   \n",
       "18                                 0                         0   \n",
       "19                                 0                         0   \n",
       "20                                 0                         0   \n",
       "21                                 0                         0   \n",
       "22                                 1                         0   \n",
       "23                                 0                         0   \n",
       "24                                 0                         0   \n",
       "25                                 0                         0   \n",
       "26                                 0                         0   \n",
       "27                                 0                         0   \n",
       "28                                 0                         0   \n",
       "29                                 0                         0   \n",
       "...                              ...                       ...   \n",
       "8263                               1                         0   \n",
       "8264                               0                         0   \n",
       "8265                               0                         0   \n",
       "8266                               0                         0   \n",
       "8267                               0                         0   \n",
       "8268                               0                         0   \n",
       "8269                               0                         0   \n",
       "8270                               0                         0   \n",
       "8271                               0                         0   \n",
       "8272                               0                         0   \n",
       "8273                               0                         0   \n",
       "8274                               0                         0   \n",
       "8275                               0                         0   \n",
       "8276                               0                         0   \n",
       "8277                               0                         0   \n",
       "8278                               0                         0   \n",
       "8279                               0                         0   \n",
       "8280                               0                         0   \n",
       "8281                               0                         0   \n",
       "8282                               0                         0   \n",
       "8283                               0                         0   \n",
       "8284                               0                         0   \n",
       "8285                               0                         0   \n",
       "8286                               0                         0   \n",
       "8287                               0                         0   \n",
       "8288                               0                         0   \n",
       "8289                               0                         0   \n",
       "8290                               0                         0   \n",
       "8291                               0                         0   \n",
       "8292                               0                         0   \n",
       "\n",
       "      EmploymentStatus_Unemployed  Gender_F  Gender_M  Location Code_Rur  \\\n",
       "0                               0         1         0                  0   \n",
       "1                               1         1         0                  0   \n",
       "2                               0         1         0                  0   \n",
       "3                               1         0         1                  0   \n",
       "4                               0         0         1                  1   \n",
       "5                               0         1         0                  1   \n",
       "6                               0         1         0                  0   \n",
       "7                               1         0         1                  0   \n",
       "8                               0         0         1                  0   \n",
       "9                               0         1         0                  0   \n",
       "10                              1         0         1                  0   \n",
       "11                              1         1         0                  0   \n",
       "12                              0         0         1                  0   \n",
       "13                              0         0         1                  0   \n",
       "14                              0         0         1                  0   \n",
       "15                              0         1         0                  1   \n",
       "16                              0         0         1                  0   \n",
       "17                              0         0         1                  0   \n",
       "18                              0         0         1                  0   \n",
       "19                              0         1         0                  0   \n",
       "20                              0         0         1                  0   \n",
       "21                              0         1         0                  0   \n",
       "22                              0         0         1                  0   \n",
       "23                              1         1         0                  0   \n",
       "24                              0         1         0                  0   \n",
       "25                              0         0         1                  0   \n",
       "26                              1         1         0                  0   \n",
       "27                              0         1         0                  0   \n",
       "28                              0         1         0                  0   \n",
       "29                              0         1         0                  0   \n",
       "...                           ...       ...       ...                ...   \n",
       "8263                            0         1         0                  0   \n",
       "8264                            1         0         1                  0   \n",
       "8265                            0         1         0                  0   \n",
       "8266                            0         1         0                  0   \n",
       "8267                            0         0         1                  0   \n",
       "8268                            0         0         1                  0   \n",
       "8269                            0         1         0                  0   \n",
       "8270                            0         1         0                  0   \n",
       "8271                            0         0         1                  0   \n",
       "8272                            0         1         0                  1   \n",
       "8273                            0         0         1                  1   \n",
       "8274                            0         0         1                  0   \n",
       "8275                            1         0         1                  0   \n",
       "8276                            1         0         1                  0   \n",
       "8277                            0         1         0                  0   \n",
       "8278                            0         0         1                  0   \n",
       "8279                            1         0         1                  0   \n",
       "8280                            0         1         0                  1   \n",
       "8281                            1         0         1                  0   \n",
       "8282                            0         0         1                  0   \n",
       "8283                            1         1         0                  0   \n",
       "8284                            0         1         0                  0   \n",
       "8285                            0         0         1                  0   \n",
       "8286                            0         0         1                  0   \n",
       "8287                            1         0         1                  0   \n",
       "8288                            0         0         1                  0   \n",
       "8289                            0         1         0                  0   \n",
       "8290                            1         0         1                  0   \n",
       "8291                            0         0         1                  0   \n",
       "8292                            1         0         1                  0   \n",
       "\n",
       "      Location Code_Sub  Location Code_Urb  Marital Status_Div  \\\n",
       "0                     1                  0                   0   \n",
       "1                     1                  0                   0   \n",
       "2                     1                  0                   0   \n",
       "3                     1                  0                   0   \n",
       "4                     0                  0                   0   \n",
       "5                     0                  0                   0   \n",
       "6                     1                  0                   0   \n",
       "7                     0                  1                   0   \n",
       "8                     1                  0                   1   \n",
       "9                     0                  1                   0   \n",
       "10                    1                  0                   0   \n",
       "11                    1                  0                   0   \n",
       "12                    0                  1                   0   \n",
       "13                    1                  0                   0   \n",
       "14                    0                  1                   0   \n",
       "15                    0                  0                   0   \n",
       "16                    1                  0                   0   \n",
       "17                    1                  0                   0   \n",
       "18                    0                  1                   0   \n",
       "19                    1                  0                   0   \n",
       "20                    1                  0                   0   \n",
       "21                    1                  0                   1   \n",
       "22                    1                  0                   1   \n",
       "23                    1                  0                   0   \n",
       "24                    1                  0                   0   \n",
       "25                    1                  0                   0   \n",
       "26                    1                  0                   0   \n",
       "27                    0                  1                   0   \n",
       "28                    1                  0                   0   \n",
       "29                    1                  0                   0   \n",
       "...                 ...                ...                 ...   \n",
       "8263                  1                  0                   0   \n",
       "8264                  1                  0                   0   \n",
       "8265                  1                  0                   1   \n",
       "8266                  1                  0                   1   \n",
       "8267                  1                  0                   1   \n",
       "8268                  1                  0                   1   \n",
       "8269                  1                  0                   0   \n",
       "8270                  0                  1                   0   \n",
       "8271                  1                  0                   1   \n",
       "8272                  0                  0                   0   \n",
       "8273                  0                  0                   0   \n",
       "8274                  0                  1                   0   \n",
       "8275                  1                  0                   0   \n",
       "8276                  1                  0                   0   \n",
       "8277                  0                  1                   1   \n",
       "8278                  1                  0                   0   \n",
       "8279                  1                  0                   0   \n",
       "8280                  0                  0                   0   \n",
       "8281                  1                  0                   0   \n",
       "8282                  1                  0                   1   \n",
       "8283                  1                  0                   0   \n",
       "8284                  1                  0                   0   \n",
       "8285                  1                  0                   0   \n",
       "8286                  1                  0                   1   \n",
       "8287                  1                  0                   1   \n",
       "8288                  1                  0                   0   \n",
       "8289                  0                  1                   0   \n",
       "8290                  1                  0                   0   \n",
       "8291                  0                  1                   0   \n",
       "8292                  1                  0                   0   \n",
       "\n",
       "      Marital Status_Mar  Marital Status_Sin  Policy Type_Corporate Auto  \\\n",
       "0                      1                   0                           1   \n",
       "1                      0                   1                           0   \n",
       "2                      1                   0                           0   \n",
       "3                      1                   0                           1   \n",
       "4                      0                   1                           0   \n",
       "5                      1                   0                           0   \n",
       "6                      1                   0                           1   \n",
       "7                      0                   1                           1   \n",
       "8                      0                   0                           1   \n",
       "9                      1                   0                           0   \n",
       "10                     0                   1                           0   \n",
       "11                     1                   0                           0   \n",
       "12                     1                   0                           1   \n",
       "13                     1                   0                           1   \n",
       "14                     0                   1                           1   \n",
       "15                     1                   0                           1   \n",
       "16                     1                   0                           0   \n",
       "17                     1                   0                           0   \n",
       "18                     1                   0                           0   \n",
       "19                     1                   0                           1   \n",
       "20                     0                   1                           0   \n",
       "21                     0                   0                           0   \n",
       "22                     0                   0                           0   \n",
       "23                     0                   1                           1   \n",
       "24                     1                   0                           1   \n",
       "25                     1                   0                           0   \n",
       "26                     0                   1                           0   \n",
       "27                     1                   0                           1   \n",
       "28                     0                   1                           0   \n",
       "29                     1                   0                           0   \n",
       "...                  ...                 ...                         ...   \n",
       "8263                   1                   0                           0   \n",
       "8264                   0                   1                           1   \n",
       "8265                   0                   0                           0   \n",
       "8266                   0                   0                           0   \n",
       "8267                   0                   0                           1   \n",
       "8268                   0                   0                           0   \n",
       "8269                   0                   1                           0   \n",
       "8270                   1                   0                           1   \n",
       "8271                   0                   0                           1   \n",
       "8272                   0                   1                           0   \n",
       "8273                   1                   0                           0   \n",
       "8274                   1                   0                           0   \n",
       "8275                   1                   0                           0   \n",
       "8276                   0                   1                           1   \n",
       "8277                   0                   0                           0   \n",
       "8278                   0                   1                           0   \n",
       "8279                   1                   0                           1   \n",
       "8280                   1                   0                           0   \n",
       "8281                   0                   1                           0   \n",
       "8282                   0                   0                           0   \n",
       "8283                   0                   1                           0   \n",
       "8284                   0                   1                           1   \n",
       "8285                   1                   0                           0   \n",
       "8286                   0                   0                           0   \n",
       "8287                   0                   0                           0   \n",
       "8288                   1                   0                           0   \n",
       "8289                   0                   1                           0   \n",
       "8290                   0                   1                           0   \n",
       "8291                   1                   0                           1   \n",
       "8292                   0                   1                           0   \n",
       "\n",
       "      Policy Type_Personal Auto  Policy Type_Special Auto  \\\n",
       "0                             0                         0   \n",
       "1                             1                         0   \n",
       "2                             1                         0   \n",
       "3                             0                         0   \n",
       "4                             1                         0   \n",
       "5                             1                         0   \n",
       "6                             0                         0   \n",
       "7                             0                         0   \n",
       "8                             0                         0   \n",
       "9                             0                         1   \n",
       "10                            1                         0   \n",
       "11                            1                         0   \n",
       "12                            0                         0   \n",
       "13                            0                         0   \n",
       "14                            0                         0   \n",
       "15                            0                         0   \n",
       "16                            1                         0   \n",
       "17                            1                         0   \n",
       "18                            1                         0   \n",
       "19                            0                         0   \n",
       "20                            1                         0   \n",
       "21                            1                         0   \n",
       "22                            1                         0   \n",
       "23                            0                         0   \n",
       "24                            0                         0   \n",
       "25                            1                         0   \n",
       "26                            1                         0   \n",
       "27                            0                         0   \n",
       "28                            1                         0   \n",
       "29                            1                         0   \n",
       "...                         ...                       ...   \n",
       "8263                          1                         0   \n",
       "8264                          0                         0   \n",
       "8265                          1                         0   \n",
       "8266                          1                         0   \n",
       "8267                          0                         0   \n",
       "8268                          1                         0   \n",
       "8269                          1                         0   \n",
       "8270                          0                         0   \n",
       "8271                          0                         0   \n",
       "8272                          1                         0   \n",
       "8273                          1                         0   \n",
       "8274                          0                         1   \n",
       "8275                          1                         0   \n",
       "8276                          0                         0   \n",
       "8277                          1                         0   \n",
       "8278                          1                         0   \n",
       "8279                          0                         0   \n",
       "8280                          1                         0   \n",
       "8281                          1                         0   \n",
       "8282                          1                         0   \n",
       "8283                          1                         0   \n",
       "8284                          0                         0   \n",
       "8285                          1                         0   \n",
       "8286                          1                         0   \n",
       "8287                          1                         0   \n",
       "8288                          1                         0   \n",
       "8289                          1                         0   \n",
       "8290                          1                         0   \n",
       "8291                          0                         0   \n",
       "8292                          1                         0   \n",
       "\n",
       "      Sales Channel_Agent  Sales Channel_Branch  Sales Channel_Call Center  \\\n",
       "0                       1                     0                          0   \n",
       "1                       1                     0                          0   \n",
       "2                       1                     0                          0   \n",
       "3                       0                     0                          1   \n",
       "4                       1                     0                          0   \n",
       "5                       0                     0                          0   \n",
       "6                       1                     0                          0   \n",
       "7                       1                     0                          0   \n",
       "8                       1                     0                          0   \n",
       "9                       0                     1                          0   \n",
       "10                      1                     0                          0   \n",
       "11                      1                     0                          0   \n",
       "12                      1                     0                          0   \n",
       "13                      0                     1                          0   \n",
       "14                      0                     0                          1   \n",
       "15                      0                     1                          0   \n",
       "16                      0                     0                          1   \n",
       "17                      0                     0                          1   \n",
       "18                      0                     1                          0   \n",
       "19                      0                     0                          1   \n",
       "20                      0                     1                          0   \n",
       "21                      0                     0                          1   \n",
       "22                      1                     0                          0   \n",
       "23                      0                     1                          0   \n",
       "24                      0                     1                          0   \n",
       "25                      0                     0                          1   \n",
       "26                      1                     0                          0   \n",
       "27                      0                     1                          0   \n",
       "28                      0                     0                          1   \n",
       "29                      0                     1                          0   \n",
       "...                   ...                   ...                        ...   \n",
       "8263                    0                     1                          0   \n",
       "8264                    1                     0                          0   \n",
       "8265                    0                     1                          0   \n",
       "8266                    1                     0                          0   \n",
       "8267                    1                     0                          0   \n",
       "8268                    0                     1                          0   \n",
       "8269                    1                     0                          0   \n",
       "8270                    1                     0                          0   \n",
       "8271                    0                     0                          1   \n",
       "8272                    0                     0                          0   \n",
       "8273                    1                     0                          0   \n",
       "8274                    0                     0                          0   \n",
       "8275                    0                     1                          0   \n",
       "8276                    1                     0                          0   \n",
       "8277                    1                     0                          0   \n",
       "8278                    0                     1                          0   \n",
       "8279                    0                     0                          1   \n",
       "8280                    0                     1                          0   \n",
       "8281                    0                     0                          1   \n",
       "8282                    0                     0                          1   \n",
       "8283                    0                     1                          0   \n",
       "8284                    0                     1                          0   \n",
       "8285                    1                     0                          0   \n",
       "8286                    1                     0                          0   \n",
       "8287                    0                     0                          1   \n",
       "8288                    1                     0                          0   \n",
       "8289                    0                     1                          0   \n",
       "8290                    0                     0                          0   \n",
       "8291                    0                     1                          0   \n",
       "8292                    0                     0                          1   \n",
       "\n",
       "      Sales Channel_Web  \n",
       "0                     0  \n",
       "1                     0  \n",
       "2                     0  \n",
       "3                     0  \n",
       "4                     0  \n",
       "5                     1  \n",
       "6                     0  \n",
       "7                     0  \n",
       "8                     0  \n",
       "9                     0  \n",
       "10                    0  \n",
       "11                    0  \n",
       "12                    0  \n",
       "13                    0  \n",
       "14                    0  \n",
       "15                    0  \n",
       "16                    0  \n",
       "17                    0  \n",
       "18                    0  \n",
       "19                    0  \n",
       "20                    0  \n",
       "21                    0  \n",
       "22                    0  \n",
       "23                    0  \n",
       "24                    0  \n",
       "25                    0  \n",
       "26                    0  \n",
       "27                    0  \n",
       "28                    0  \n",
       "29                    0  \n",
       "...                 ...  \n",
       "8263                  0  \n",
       "8264                  0  \n",
       "8265                  0  \n",
       "8266                  0  \n",
       "8267                  0  \n",
       "8268                  0  \n",
       "8269                  0  \n",
       "8270                  0  \n",
       "8271                  0  \n",
       "8272                  1  \n",
       "8273                  0  \n",
       "8274                  1  \n",
       "8275                  0  \n",
       "8276                  0  \n",
       "8277                  0  \n",
       "8278                  0  \n",
       "8279                  0  \n",
       "8280                  0  \n",
       "8281                  0  \n",
       "8282                  0  \n",
       "8283                  0  \n",
       "8284                  0  \n",
       "8285                  0  \n",
       "8286                  0  \n",
       "8287                  0  \n",
       "8288                  0  \n",
       "8289                  0  \n",
       "8290                  1  \n",
       "8291                  0  \n",
       "8292                  0  \n",
       "\n",
       "[8293 rows x 40 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = data_dummies.loc[:, 'Customer Lifetime Value':'Sales Channel_Web']\n",
    "display(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Импортируем из модуля sklearn.model_selection функцию train_test_split\n",
    "from sklearn.model_selection import train_test_split\n",
    "# Выполняем разбиение на обучение и контроль\n",
    "X_train, X_control, y_train, y_control = train_test_split(X, y, test_size=0.3, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    5229\n",
      "1     576\n",
      "Name: Response_Yes, dtype: int64\n",
      "0    2233\n",
      "1     255\n",
      "Name: Response_Yes, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(y_train.value_counts())\n",
    "print(y_control.value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Параметры случайного леса и подгонка модели"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "forest=RandomForestClassifier(random_state=152)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
       "            max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "            min_impurity_split=1e-07, min_samples_leaf=1,\n",
       "            min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "            n_estimators=10, n_jobs=1, oob_score=False, random_state=152,\n",
       "            verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forest.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Правильность на обучающей выборке: 0.986\n",
      "Правильность на контрольной выборке: 0.922\n"
     ]
    }
   ],
   "source": [
    "print(\"Правильность на обучающей выборке: {:.3f}\".format(forest.score(X_train, y_train)))\n",
    "print(\"Правильность на контрольной выборке: {:.3f}\".format(forest.score(X_control, y_control)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Правильность на обучающей выборке: 0.992\n",
      "OOB оценка правильности: 0.94\n",
      "Правильность на контрольной выборке: 0.926\n"
     ]
    }
   ],
   "source": [
    "forest2 = RandomForestClassifier(n_estimators=300, oob_score=True, random_state=152)\n",
    "forest2.fit(X_train, y_train)\n",
    "print(\"Правильность на обучающей выборке: {:.3f}\".format(forest2.score(X_train, y_train)))\n",
    "print(\"OOB оценка правильности: {:.2f}\".format(forest2.oob_score_))\n",
    "print(\"Правильность на контрольной выборке: {:.3f}\".format(forest2.score(X_control, y_control)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Важности предикторов "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.10665255  0.09429739  0.09375851  0.08265336  0.09315791  0.01939205\n",
      "  0.04232704  0.0225786   0.02886791  0.01594937  0.02777498  0.01336178\n",
      "  0.0127373   0.01287837  0.0077335   0.01408216  0.01477403  0.00963991\n",
      "  0.01391571  0.00809341  0.00501552  0.00955632  0.00604601  0.04330566\n",
      "  0.00753809  0.01495914  0.01540667  0.00616867  0.01111844  0.00596849\n",
      "  0.01331914  0.01478345  0.01312962  0.02255217  0.02371224  0.00834518\n",
      "  0.01760693  0.01024394  0.00788615  0.00871231]\n"
     ]
    }
   ],
   "source": [
    "print(forest2.feature_importances_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1) Customer Lifetime Value             0.106653\n",
      " 2) Income                              0.094297\n",
      " 3) Monthly Premium Auto                0.093759\n",
      " 4) Months Since Policy Inception       0.093158\n",
      " 5) Months Since Last Claim             0.082653\n",
      " 6) EmploymentStatus_Retired            0.043306\n",
      " 7) Number of Policies                  0.042327\n",
      " 8) State_California                    0.028868\n",
      " 9) State_Oregon                        0.027775\n",
      "10) Policy Type_Personal Auto           0.023712\n",
      "11) State_Arizona                       0.022579\n",
      "12) Policy Type_Corporate Auto          0.022552\n",
      "13) Number of Open Complaints           0.019392\n",
      "14) Sales Channel_Agent                 0.017607\n",
      "15) State_Nevada                        0.015949\n",
      "16) Gender_M                            0.015407\n",
      "17) Gender_F                            0.014959\n",
      "18) Marital Status_Mar                  0.014783\n",
      "19) Education_College                   0.014774\n",
      "20) Education_Bachelor                  0.014082\n",
      "21) Education_High School or Below      0.013916\n",
      "22) State_Washington                    0.013362\n",
      "23) Marital Status_Div                  0.013319\n",
      "24) Marital Status_Sin                  0.013130\n",
      "25) Coverage_Extended                   0.012878\n",
      "26) Coverage_Basic                      0.012737\n",
      "27) Location Code_Sub                   0.011118\n",
      "28) Sales Channel_Branch                0.010244\n",
      "29) Education_Doctor                    0.009640\n",
      "30) EmploymentStatus_Employed           0.009556\n",
      "31) Sales Channel_Web                   0.008712\n",
      "32) Policy Type_Special Auto            0.008345\n",
      "33) Education_Master                    0.008093\n",
      "34) Sales Channel_Call Center           0.007886\n",
      "35) Coverage_Premium                    0.007734\n",
      "36) EmploymentStatus_Unemployed         0.007538\n",
      "37) Location Code_Rur                   0.006169\n",
      "38) EmploymentStatus_Medical Leave      0.006046\n",
      "39) Location Code_Urb                   0.005968\n",
      "40) EmploymentStatus_Disabled           0.005016\n"
     ]
    }
   ],
   "source": [
    "# Создаем объект с названиями предикторов\n",
    "feat_labels = X.columns\n",
    "# Создаем объект со значениями важностей, вычисленными моделью forest2\n",
    "importances = forest2.feature_importances_\n",
    "# Задаем сортировку значений важности и сопоставляем названия предикторов важностям\n",
    "indices = np.argsort(importances)[::-1]\n",
    "for f in range(X_train.shape[1]):\n",
    "    print(\"%2d) %-*s %f\" % (f + 1, 35,\n",
    "                            feat_labels[indices[f]],\n",
    "                            importances[indices[f]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6sjAhRn8RGSQi+8Xr+VeN9mx3ROQhEVm9PY7dWkTkahFZtaKsiMi3wyohRWV6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tRErQeAma2EzCveQDhUv0VMzQaIcd9qGP2U+hvLlIiQMYiB1Ls90TCw6wD9NDbMQ5tcT0BTtBGM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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc0ef907f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Задаем заголовок диаграммы\n",
    "plt.title('Важности предикторов')\n",
    "# Настраиваем столбики  \n",
    "plt.bar(range(X_train.shape[1]), importances[indices],\n",
    "              color='lightblue', align='center')\n",
    "# Настраиваем метки оси x \n",
    "plt.xticks(range(X_train.shape[1]),\n",
    "           feat_labels[indices], rotation=90)\n",
    "# Задаем пределы значений оси x\n",
    "plt.xlim([-1, X_train.shape[1]])\n",
    "# Функция tight_layout позволяет оптимально позиционировать элементы графика на рисунке,\n",
    "# например, чтобы метки оси не наезжали друг друга и пр. \n",
    "plt.tight_layout()\n",
    "# Выводим диаграмму\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Прогнозы модели и матрица ошибок"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Матрица ошибок:\n",
      "[[2159   74]\n",
      " [ 111  144]]\n"
     ]
    }
   ],
   "source": [
    "# Вычисляем с помощью метода predict прогнозы для контрольной выборки \n",
    "# и записываем в объект pred_forest2\n",
    "pred_forest2 = forest2.predict(X_control)\n",
    "# Из модуля sklearn.metrics импортируем функцию confusion_matrix\n",
    "from sklearn.metrics import confusion_matrix\n",
    "# Вычисляем матрицу ошибок, передав функции confusion_matrix в качестве аргументов \n",
    "# фактические значения зависимой переменной, записанные в y_control, и спрогнозированные \n",
    "# значения зависимой переменной, записанные в pred_forest2\n",
    "confusion = confusion_matrix(y_control, pred_forest2)\n",
    "# Печатаем матрицу ошибок\n",
    "print(\"Матрица ошибок:\\n{}\".format(confusion))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Отчет о результатах классификации: точность, полнота и F-мера"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                precision    recall  f1-score   support\n",
      "\n",
      "Не откликнулся       0.95      0.97      0.96      2233\n",
      "   Откликнулся       0.66      0.56      0.61       255\n",
      "\n",
      "   avg / total       0.92      0.93      0.92      2488\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Из модуля sklearn.metrics импортируем функцию classification_report\n",
    "from sklearn.metrics import classification_report\n",
    "# Вычисляем значения точности, полноты и f-меры для классов и печатаем их\n",
    "print(classification_report(y_control, pred_forest2,\n",
    "                            target_names=[\"Не откликнулся\", \"Откликнулся\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Построение ROC-кривой и выбор оптимального порога"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Форма вероятностей: (2488, 2)\n"
     ]
    }
   ],
   "source": [
    "# Вычисляем с помощью метода predict_proba прогнозы\n",
    "# для контрольной выборки и печатаем их\n",
    "print(\"Форма вероятностей: {}\".format(forest2.predict_proba(X_control).shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Спрогнозированные вероятности:\n",
      "[[ 0.94222222  0.05777778]\n",
      " [ 0.98        0.02      ]\n",
      " [ 0.95638889  0.04361111]\n",
      " [ 0.91666667  0.08333333]\n",
      " [ 0.93388889  0.06611111]]\n"
     ]
    }
   ],
   "source": [
    "# Выведем первые несколько элементов predict_proba\n",
    "print(\"Спрогнозированные вероятности:\\n{}\".format(forest2.predict_proba(X_control[:5])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cc13049fd0>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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WdhQiIiKJr7ItIWcBh7n7kIoSEAB3/9jdzwN+DwyIRoDxZMkSeP99OPXUsCMRERFJfJXt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\nwywAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc13049f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Из модуля sklearn.metrics импортируем функцию roc_curve\n",
    "from sklearn.metrics import roc_curve\n",
    "# Вычисляем значения FPR и TPR для всех возможных порогов отсечения, передав функции \n",
    "# roc_curve в качестве аргументов фактические значения зависимой переменной, \n",
    "# записанные в y_control, и вероятности положительного класса, вычисленные \n",
    "# с помощью метода predict_proba\n",
    "fpr_rf, tpr_rf, thresholds_rf = roc_curve(y_control, forest2.predict_proba(X_control)[:, 1])\n",
    "\n",
    "# Создаем заголовок ROC-кривой\n",
    "plt.plot(fpr_rf, tpr_rf, label=\"ROC-кривая RF\")\n",
    "# Задаем название для оси x\n",
    "plt.xlabel(\"FPR\")\n",
    "# Задаем название для оси y\n",
    "plt.ylabel(\"TPR (полнота)\")\n",
    "# Задаем порог отсечения по умолчанию 0.5\n",
    "close_default_rf = np.argmin(np.abs(thresholds_rf - 0.5))\n",
    "# Строим ROC-кривую и наносим порог отсечения 0.5\n",
    "plt.plot(fpr_rf[close_default_rf], tpr_rf[close_default_rf], '^', markersize=10,\n",
    "         label=\"порог 0.5 RF\", fillstyle=\"none\", c='k', mew=2)\n",
    "# Задаем расположение легенды\n",
    "plt.legend(loc=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Значение AUC для контрольной выборки: 0.936\n"
     ]
    }
   ],
   "source": [
    "# Из модуля sklearn.metrics импортируем функцию roc_auc_score\n",
    "from sklearn.metrics import roc_auc_score\n",
    "# Вычисляем значение AUC, передав функции roc_curve в качестве аргументов\n",
    "# фактические значения зависимой переменной, записанные в y_control, \n",
    "# и вероятности положительного класса, вычисленные с помощью метода predict_proba\n",
    "rf_auc = roc_auc_score(y_control, forest2.predict_proba(X_control)[:, 1])\n",
    "# Печатаем значение AUC\n",
    "print(\"Значение AUC для контрольной выборки: {:.3f}\".format(rf_auc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_pred_lower_threshold = forest2.predict_proba(X_control)[:, 1] > .3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Матрица ошибок для порога 0.3:\n",
      "[[2116  117]\n",
      " [  56  199]]\n"
     ]
    }
   ],
   "source": [
    "confusion2 = confusion_matrix(y_control, y_pred_lower_threshold)\n",
    "print(\"Матрица ошибок для порога 0.3:\\n{}\".format(confusion2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cc12fe3ac8>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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pQElIIWvWQEYG1FZ3XRERkbhTElLI0qXQuTOk6aqIiIjEnb5uC3FXK4iIiEh1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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc12fe3550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve\n",
    "fpr_rf2, tpr_rf2, thresholds_rf2 = roc_curve(y_control, forest2.predict_proba(X_control)[:, 1])\n",
    "\n",
    "plt.plot(fpr_rf2, tpr_rf2, label=\"ROC-кривая RF\")\n",
    "\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR (полнота)\")\n",
    "close_default_rf2 = np.argmin(np.abs(thresholds_rf2 - 0.3))\n",
    "plt.plot(fpr_rf2[close_default_rf2], tpr_rf2[close_default_rf2], '^', markersize=10,\n",
    "         label=\"порог 0.3 RF\", fillstyle=\"none\", c='k', mew=2)\n",
    "plt.legend(loc=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Сравнение модели случайного леса с моделью дерева решений"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Правильность на обучающей выборке: 0.992\n",
      "Правильность на контрольной выборке: 0.897\n"
     ]
    }
   ],
   "source": [
    "tree = DecisionTreeClassifier(random_state=152)\n",
    "tree.fit(X_train, y_train)\n",
    "print(\"Правильность на обучающей выборке: {:.3f}\".format(tree.score(X_train, y_train)))\n",
    "print(\"Правильность на контрольной выборке: {:.3f}\".format(tree.score(X_control, y_control)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC на обучающей выборке: 1.000\n",
      "AUC на контрольной выборке: 0.793\n"
     ]
    }
   ],
   "source": [
    "tree = DecisionTreeClassifier(random_state=152)\n",
    "tree.fit(X_train, y_train)\n",
    "print(\"AUC на обучающей выборке: {:.3f}\".\n",
    "      format(roc_auc_score(y_train, tree.predict_proba(X_train)[:, 1])))\n",
    "print(\"AUC на контрольной выборке: {:.3f}\".\n",
    "      format(roc_auc_score(y_control, tree.predict_proba(X_control)[:, 1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC на обучающей выборке: 0.940\n",
      "AUC на контрольной выборке: 0.881\n"
     ]
    }
   ],
   "source": [
    "tree2 = DecisionTreeClassifier(max_depth=15, min_samples_leaf=15, \n",
    "                               min_samples_split=30, random_state=152)\n",
    "tree2.fit(X_train, y_train)\n",
    "print(\"AUC на обучающей выборке: {:.3f}\".\n",
    "      format(roc_auc_score(y_train, tree2.predict_proba(X_train)[:, 1])))\n",
    "print(\"AUC на контрольной выборке: {:.3f}\".\n",
    "      format(roc_auc_score(y_control, tree2.predict_proba(X_control)[:, 1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1) Customer Lifetime Value             0.180057\n",
      " 2) Income                              0.178451\n",
      " 3) EmploymentStatus_Retired            0.158791\n",
      " 4) Months Since Policy Inception       0.105343\n",
      " 5) Monthly Premium Auto                0.094024\n",
      " 6) Months Since Last Claim             0.079937\n",
      " 7) Sales Channel_Agent                 0.024098\n",
      " 8) Coverage_Basic                      0.021395\n",
      " 9) Marital Status_Div                  0.020491\n",
      "10) Location Code_Sub                   0.018467\n",
      "11) Education_Doctor                    0.016785\n",
      "12) Education_College                   0.016195\n",
      "13) Number of Policies                  0.013490\n",
      "14) Gender_M                            0.013051\n",
      "15) Number of Open Complaints           0.007786\n",
      "16) Sales Channel_Branch                0.007532\n",
      "17) EmploymentStatus_Disabled           0.007500\n",
      "18) EmploymentStatus_Employed           0.007349\n",
      "19) Marital Status_Sin                  0.006384\n",
      "20) Marital Status_Mar                  0.005360\n",
      "21) Education_High School or Below      0.005183\n",
      "22) Education_Master                    0.004326\n",
      "23) Sales Channel_Web                   0.003230\n",
      "24) Education_Bachelor                  0.002402\n",
      "25) Sales Channel_Call Center           0.001451\n",
      "26) State_California                    0.000851\n",
      "27) Coverage_Premium                    0.000071\n",
      "28) Coverage_Extended                   0.000000\n",
      "29) EmploymentStatus_Unemployed         0.000000\n",
      "30) State_Washington                    0.000000\n",
      "31) State_Oregon                        0.000000\n",
      "32) State_Nevada                        0.000000\n",
      "33) EmploymentStatus_Medical Leave      0.000000\n",
      "34) State_Arizona                       0.000000\n",
      "35) Gender_F                            0.000000\n",
      "36) Location Code_Rur                   0.000000\n",
      "37) Location Code_Urb                   0.000000\n",
      "38) Policy Type_Corporate Auto          0.000000\n",
      "39) Policy Type_Personal Auto           0.000000\n",
      "40) Policy Type_Special Auto            0.000000\n"
     ]
    }
   ],
   "source": [
    "feat_labels = X.columns\n",
    "importances =  tree2.feature_importances_\n",
    "indices = np.argsort(importances)[::-1]\n",
    "for f in range(X_train.shape[1]):\n",
    "    print(\"%2d) %-*s %f\" % (f + 1, 35,\n",
    "                            feat_labels[indices[f]],\n",
    "                            importances[indices[f]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Из модуля sklearn.tree импортируем функцию export_graphviz\n",
    "from sklearn.tree import export_graphviz\n",
    "# С помощью функции export_graphviz на основе модели tree2 создаем файл в формате .dot, \n",
    "# предназначенный для описания диаграммы дерева\n",
    "export_graphviz(tree2, out_file=\"tree2.dot\", class_names=[\"no response\", \"response\"],\n",
    "                feature_names=feat_labels, impurity=False, filled=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\r\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n",
       "<!-- Generated by graphviz version 2.38.0 (20140413.2041)\r\n",
       " -->\r\n",
       "<!-- Title: Tree Pages: 1 -->\r\n",
       "<svg width=\"8561pt\" height=\"1621pt\"\r\n",
       " viewBox=\"0.00 0.00 8561.00 1621.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 1617)\">\r\n",
       "<title>Tree</title>\r\n",
       "<polygon fill=\"white\" stroke=\"none\" points=\"-4,4 -4,-1617 8557,-1617 8557,4 -4,4\"/>\r\n",
       "<!-- 0 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6464\" y=\"-1597.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">EmploymentStatus_Retired &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6464\" y=\"-1582.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 5805</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6464\" y=\"-1567.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [5229, 576]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6464\" y=\"-1552.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 1 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6332\" y=\"-1493.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Sales Channel_Agent &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6332\" y=\"-1478.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 5620</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6332\" y=\"-1463.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [5137, 483]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6332\" y=\"-1448.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 0&#45;&gt;1 -->\r\n",
       "<g id=\"edge1\" class=\"edge\"><title>0&#45;&gt;1</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6421.14,-1544.88C6409.04,-1535.53 6395.75,-1525.26 6383.21,-1515.57\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6378.27\" y=\"-1530.4\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">True</text>\r\n",
       "</g>\r\n",
       "<!-- 268 -->\r\n",
       "<g id=\"node269\" class=\"node\"><title>268</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"6696\" y=\"-1493.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 67.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6696\" y=\"-1478.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 185</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6696\" y=\"-1463.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [92, 93]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6696\" y=\"-1448.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 0&#45;&gt;268 -->\r\n",
       "<g id=\"edge268\" class=\"edge\"><title>0&#45;&gt;268</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6539.32,-1544.88C6562.33,-1534.77 6587.79,-1523.58 6611.37,-1513.21\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6611.59\" y=\"-1528.72\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">False</text>\r\n",
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       "<!-- 2 -->\r\n",
       "<g id=\"node3\" class=\"node\"><title>2</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"2257\" y=\"-1389.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 11879.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2257\" y=\"-1374.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 3523</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2257\" y=\"-1359.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [3299, 224]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2257\" y=\"-1344.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 1&#45;&gt;2 -->\r\n",
       "<g id=\"edge2\" class=\"edge\"><title>1&#45;&gt;2</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6243.58,-1471.79C5701.34,-1458.21 2832.61,-1386.41 2331.66,-1373.87\"/>\r\n",
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       "<!-- 161 -->\r\n",
       "<g id=\"node162\" class=\"node\"><title>161</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.858824\" stroke=\"black\" points=\"6433.5,-1405 6230.5,-1405 6230.5,-1337 6433.5,-1337 6433.5,-1405\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6332\" y=\"-1389.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 209.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6332\" y=\"-1374.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 2097</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6332\" y=\"-1359.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [1838, 259]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6332\" y=\"-1344.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 1&#45;&gt;161 -->\r\n",
       "<g id=\"edge161\" class=\"edge\"><title>1&#45;&gt;161</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6332,-1440.88C6332,-1432.78 6332,-1423.98 6332,-1415.47\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"6335.5,-1415.3 6332,-1405.3 6328.5,-1415.3 6335.5,-1415.3\"/>\r\n",
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       "<!-- 3 -->\r\n",
       "<g id=\"node4\" class=\"node\"><title>3</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.972549\" stroke=\"black\" points=\"1667,-1301 1461,-1301 1461,-1233 1667,-1233 1667,-1301\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1564\" y=\"-1285.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 34.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1564\" y=\"-1270.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 900</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1564\" y=\"-1255.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [877, 23]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1564\" y=\"-1240.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 2&#45;&gt;3 -->\r\n",
       "<g id=\"edge3\" class=\"edge\"><title>2&#45;&gt;3</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2192.74,-1360.54C2075.15,-1343.23 1823.97,-1306.26 1677.17,-1284.66\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1677.62,-1281.19 1667.22,-1283.19 1676.6,-1288.11 1677.62,-1281.19\"/>\r\n",
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       "<!-- 30 -->\r\n",
       "<g id=\"node31\" class=\"node\"><title>30</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.917647\" stroke=\"black\" points=\"2343,-1301 2171,-1301 2171,-1233 2343,-1233 2343,-1301\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2257\" y=\"-1285.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Location Code_Sub &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2257\" y=\"-1270.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 2623</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2257\" y=\"-1255.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [2422, 201]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2257\" y=\"-1240.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 2&#45;&gt;30 -->\r\n",
       "<g id=\"edge30\" class=\"edge\"><title>2&#45;&gt;30</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2257,-1336.88C2257,-1328.78 2257,-1319.98 2257,-1311.47\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2260.5,-1311.3 2257,-1301.3 2253.5,-1311.3 2260.5,-1311.3\"/>\r\n",
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       "<!-- 4 -->\r\n",
       "<g id=\"node5\" class=\"node\"><title>4</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.980392\" stroke=\"black\" points=\"1190,-1197 1030,-1197 1030,-1129 1190,-1129 1190,-1197\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-1181.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Marital Status_Sin &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-1166.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 881</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-1151.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [863, 18]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-1136.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 3&#45;&gt;4 -->\r\n",
       "<g id=\"edge4\" class=\"edge\"><title>3&#45;&gt;4</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1460.98,-1242.85C1382.36,-1225.19 1275.12,-1201.1 1199.94,-1184.21\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1200.54,-1180.75 1190.02,-1181.98 1199,-1187.58 1200.54,-1180.75\"/>\r\n",
       "</g>\r\n",
       "<!-- 29 -->\r\n",
       "<g id=\"node30\" class=\"node\"><title>29</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.643137\" stroke=\"black\" points=\"1628,-1189.5 1500,-1189.5 1500,-1136.5 1628,-1136.5 1628,-1189.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1564\" y=\"-1174.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 19</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1564\" y=\"-1159.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 5]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1564\" y=\"-1144.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 3&#45;&gt;29 -->\r\n",
       "<g id=\"edge29\" class=\"edge\"><title>3&#45;&gt;29</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1564,-1232.88C1564,-1222.33 1564,-1210.6 1564,-1199.85\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1567.5,-1199.52 1564,-1189.52 1560.5,-1199.52 1567.5,-1199.52\"/>\r\n",
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       "<!-- 5 -->\r\n",
       "<g id=\"node6\" class=\"node\"><title>5</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.956863\" stroke=\"black\" points=\"750,-1093 520,-1093 520,-1025 750,-1025 750,-1093\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-1077.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 5.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-1062.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 388</text>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-1047.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [372, 16]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-1032.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 4&#45;&gt;5 -->\r\n",
       "<g id=\"edge5\" class=\"edge\"><title>4&#45;&gt;5</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1029.96,-1144.81C956.205,-1128.97 845.577,-1105.22 760.149,-1086.87\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"760.636,-1083.4 750.124,-1084.72 759.166,-1090.24 760.636,-1083.4\"/>\r\n",
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       "<!-- 22 -->\r\n",
       "<g id=\"node23\" class=\"node\"><title>22</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.996078\" stroke=\"black\" points=\"1193,-1093 1027,-1093 1027,-1025 1193,-1025 1193,-1093\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-1077.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Number of Policies &lt;= 8.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-1062.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 493</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-1047.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [491, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-1032.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 4&#45;&gt;22 -->\r\n",
       "<g id=\"edge22\" class=\"edge\"><title>4&#45;&gt;22</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1110,-1128.88C1110,-1120.78 1110,-1111.98 1110,-1103.47\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1113.5,-1103.3 1110,-1093.3 1106.5,-1103.3 1113.5,-1103.3\"/>\r\n",
       "</g>\r\n",
       "<!-- 6 -->\r\n",
       "<g id=\"node7\" class=\"node\"><title>6</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"450\" y=\"-966.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 16</text>\r\n",
       "<text text-anchor=\"middle\" x=\"450\" y=\"-951.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [13, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"450\" y=\"-936.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 5&#45;&gt;6 -->\r\n",
       "<g id=\"edge6\" class=\"edge\"><title>5&#45;&gt;6</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M574.936,-1024.88C552.495,-1012.51 527.139,-998.53 505.161,-986.413\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"506.733,-983.283 496.286,-981.52 503.353,-989.413 506.733,-983.283\"/>\r\n",
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       "<!-- 7 -->\r\n",
       "<g id=\"node8\" class=\"node\"><title>7</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.964706\" stroke=\"black\" points=\"738,-989 532,-989 532,-921 738,-921 738,-989\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Sales Channel_Call Center &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 372</text>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [359, 13]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 5&#45;&gt;7 -->\r\n",
       "<g id=\"edge7\" class=\"edge\"><title>5&#45;&gt;7</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M635,-1024.88C635,-1016.78 635,-1007.98 635,-999.472\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"638.5,-999.299 635,-989.299 631.5,-999.299 638.5,-999.299\"/>\r\n",
       "</g>\r\n",
       "<!-- 8 -->\r\n",
       "<g id=\"node9\" class=\"node\"><title>8</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.984314\" stroke=\"black\" points=\"479.5,-885 242.5,-885 242.5,-817 479.5,-817 479.5,-885\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"361\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 91.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"361\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 252</text>\r\n",
       "<text text-anchor=\"middle\" x=\"361\" y=\"-839.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [248, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"361\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 7&#45;&gt;8 -->\r\n",
       "<g id=\"edge8\" class=\"edge\"><title>7&#45;&gt;8</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M546.04,-920.884C518.383,-910.588 487.735,-899.179 459.469,-888.656\"/>\r\n",
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       "<!-- 15 -->\r\n",
       "<g id=\"node16\" class=\"node\"><title>15</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.917647\" stroke=\"black\" points=\"718,-885 552,-885 552,-817 718,-817 718,-885\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Number of Policies &lt;= 4.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 120</text>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-839.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [111, 9]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"635\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 7&#45;&gt;15 -->\r\n",
       "<g id=\"edge15\" class=\"edge\"><title>7&#45;&gt;15</title>\r\n",
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       "<g id=\"node10\" class=\"node\"><title>9</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.992157\" stroke=\"black\" points=\"278.5,-781 41.5,-781 41.5,-713 278.5,-713 278.5,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"160\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 2431.0674</text>\r\n",
       "<text text-anchor=\"middle\" x=\"160\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 229</text>\r\n",
       "<text text-anchor=\"middle\" x=\"160\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [227, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"160\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 8&#45;&gt;9 -->\r\n",
       "<g id=\"edge9\" class=\"edge\"><title>8&#45;&gt;9</title>\r\n",
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       "<!-- 14 -->\r\n",
       "<g id=\"node15\" class=\"node\"><title>14</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"361\" y=\"-758.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 23</text>\r\n",
       "<text text-anchor=\"middle\" x=\"361\" y=\"-743.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [21, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"361\" y=\"-728.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 8&#45;&gt;14 -->\r\n",
       "<g id=\"edge14\" class=\"edge\"><title>8&#45;&gt;14</title>\r\n",
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       "<!-- 10 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"64\" y=\"-654.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"64\" y=\"-639.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"64\" y=\"-624.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 9&#45;&gt;10 -->\r\n",
       "<g id=\"edge10\" class=\"edge\"><title>9&#45;&gt;10</title>\r\n",
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       "<!-- 11 -->\r\n",
       "<g id=\"node12\" class=\"node\"><title>11</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.996078\" stroke=\"black\" points=\"376,-677 146,-677 146,-609 376,-609 376,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"261\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 9.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"261\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 214</text>\r\n",
       "<text text-anchor=\"middle\" x=\"261\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [213, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"261\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 9&#45;&gt;11 -->\r\n",
       "<g id=\"edge11\" class=\"edge\"><title>9&#45;&gt;11</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M192.792,-712.884C201.7,-703.887 211.45,-694.041 220.72,-684.678\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"188\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"188\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"188\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 11&#45;&gt;12 -->\r\n",
       "<g id=\"edge12\" class=\"edge\"><title>11&#45;&gt;12</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M237.299,-608.884C229.271,-597.666 220.296,-585.126 212.227,-573.852\"/>\r\n",
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       "<!-- 13 -->\r\n",
       "<g id=\"node14\" class=\"node\"><title>13</title>\r\n",
       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"398,-565.5 270,-565.5 270,-512.5 398,-512.5 398,-565.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"334\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 199</text>\r\n",
       "<text text-anchor=\"middle\" x=\"334\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [199, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"334\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 11&#45;&gt;13 -->\r\n",
       "<g id=\"edge13\" class=\"edge\"><title>11&#45;&gt;13</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M284.701,-608.884C292.729,-597.666 301.704,-585.126 309.773,-573.852\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"312.762,-575.689 315.736,-565.52 307.07,-571.615 312.762,-575.689\"/>\r\n",
       "</g>\r\n",
       "<!-- 16 -->\r\n",
       "<g id=\"node17\" class=\"node\"><title>16</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.964706\" stroke=\"black\" points=\"680.5,-781 443.5,-781 443.5,-713 680.5,-713 680.5,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"562\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 2484.1099</text>\r\n",
       "<text text-anchor=\"middle\" x=\"562\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 92</text>\r\n",
       "<text text-anchor=\"middle\" x=\"562\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [89, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"562\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 15&#45;&gt;16 -->\r\n",
       "<g id=\"edge16\" class=\"edge\"><title>15&#45;&gt;16</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M611.299,-816.884C605.052,-808.154 598.231,-798.625 591.711,-789.514\"/>\r\n",
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       "<!-- 21 -->\r\n",
       "<g id=\"node22\" class=\"node\"><title>21</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.725490\" stroke=\"black\" points=\"827,-773.5 699,-773.5 699,-720.5 827,-720.5 827,-773.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"763\" y=\"-758.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 28</text>\r\n",
       "<text text-anchor=\"middle\" x=\"763\" y=\"-743.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [22, 6]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"763\" y=\"-728.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 15&#45;&gt;21 -->\r\n",
       "<g id=\"edge21\" class=\"edge\"><title>15&#45;&gt;21</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M676.558,-816.884C691.463,-805.006 708.228,-791.646 722.999,-779.876\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"725.336,-782.489 730.975,-773.52 720.973,-777.015 725.336,-782.489\"/>\r\n",
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       "<!-- 17 -->\r\n",
       "<g id=\"node18\" class=\"node\"><title>17</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.847059\" stroke=\"black\" points=\"574,-669.5 446,-669.5 446,-616.5 574,-616.5 574,-669.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"510\" y=\"-654.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"510\" y=\"-639.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [13, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"510\" y=\"-624.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 16&#45;&gt;17 -->\r\n",
       "<g id=\"edge17\" class=\"edge\"><title>16&#45;&gt;17</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M545.117,-712.884C539.51,-701.886 533.256,-689.617 527.597,-678.517\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"530.67,-676.839 523.01,-669.52 524.434,-680.019 530.67,-676.839\"/>\r\n",
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       "<!-- 18 -->\r\n",
       "<g id=\"node19\" class=\"node\"><title>18</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.988235\" stroke=\"black\" points=\"829.5,-677 592.5,-677 592.5,-609 829.5,-609 829.5,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"711\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 12809.793</text>\r\n",
       "<text text-anchor=\"middle\" x=\"711\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 77</text>\r\n",
       "<text text-anchor=\"middle\" x=\"711\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [76, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"711\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 16&#45;&gt;18 -->\r\n",
       "<g id=\"edge18\" class=\"edge\"><title>16&#45;&gt;18</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M610.376,-712.884C624.37,-703.304 639.771,-692.761 654.227,-682.864\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"656.337,-685.662 662.612,-677.125 652.383,-679.885 656.337,-685.662\"/>\r\n",
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       "<!-- 19 -->\r\n",
       "<g id=\"node20\" class=\"node\"><title>19</title>\r\n",
       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"662,-565.5 534,-565.5 534,-512.5 662,-512.5 662,-565.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"598\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 62</text>\r\n",
       "<text text-anchor=\"middle\" x=\"598\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [62, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"598\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 18&#45;&gt;19 -->\r\n",
       "<g id=\"edge19\" class=\"edge\"><title>18&#45;&gt;19</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M674.312,-608.884C661.397,-597.226 646.901,-584.141 634.04,-572.532\"/>\r\n",
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       "<!-- 20 -->\r\n",
       "<g id=\"node21\" class=\"node\"><title>20</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.929412\" stroke=\"black\" points=\"808,-565.5 680,-565.5 680,-512.5 808,-512.5 808,-565.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"744\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"744\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"744\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 18&#45;&gt;20 -->\r\n",
       "<g id=\"edge20\" class=\"edge\"><title>18&#45;&gt;20</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M721.714,-608.884C725.201,-598.106 729.083,-586.108 732.617,-575.184\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"735.995,-576.112 735.744,-565.52 729.335,-573.957 735.995,-576.112\"/>\r\n",
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       "<!-- 23 -->\r\n",
       "<g id=\"node24\" class=\"node\"><title>23</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.996078\" stroke=\"black\" points=\"1128.5,-989 891.5,-989 891.5,-921 1128.5,-921 1128.5,-989\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1010\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 2395.7261</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1010\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 470</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1010\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [469, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1010\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 22&#45;&gt;23 -->\r\n",
       "<g id=\"edge23\" class=\"edge\"><title>22&#45;&gt;23</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1077.53,-1024.88C1068.71,-1015.89 1059.06,-1006.04 1049.88,-996.678\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1052.15,-993.99 1042.65,-989.299 1047.15,-998.89 1052.15,-993.99\"/>\r\n",
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       "<!-- 28 -->\r\n",
       "<g id=\"node29\" class=\"node\"><title>28</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.952941\" stroke=\"black\" points=\"1275,-981.5 1147,-981.5 1147,-928.5 1275,-928.5 1275,-981.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1211\" y=\"-966.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 23</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1211\" y=\"-951.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [22, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1211\" y=\"-936.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 22&#45;&gt;28 -->\r\n",
       "<g id=\"edge28\" class=\"edge\"><title>22&#45;&gt;28</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1142.79,-1024.88C1154.23,-1013.34 1167.05,-1000.39 1178.46,-988.86\"/>\r\n",
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       "<!-- 24 -->\r\n",
       "<g id=\"node25\" class=\"node\"><title>24</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.976471\" stroke=\"black\" points=\"1027.5,-885 790.5,-885 790.5,-817 1027.5,-817 1027.5,-885\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"909\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 27.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"909\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 46</text>\r\n",
       "<text text-anchor=\"middle\" x=\"909\" y=\"-839.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [45, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"909\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 23&#45;&gt;24 -->\r\n",
       "<g id=\"edge24\" class=\"edge\"><title>23&#45;&gt;24</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M977.208,-920.884C968.3,-911.887 958.55,-902.041 949.28,-892.678\"/>\r\n",
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       "<!-- 27 -->\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"1174,-877.5 1046,-877.5 1046,-824.5 1174,-824.5 1174,-877.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 424</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [424, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1110\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 23&#45;&gt;27 -->\r\n",
       "<g id=\"edge27\" class=\"edge\"><title>23&#45;&gt;27</title>\r\n",
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       "<g id=\"node26\" class=\"node\"><title>25</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.929412\" stroke=\"black\" points=\"973,-773.5 845,-773.5 845,-720.5 973,-720.5 973,-773.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"909\" y=\"-758.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"909\" y=\"-743.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"909\" y=\"-728.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 24&#45;&gt;25 -->\r\n",
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       "<path fill=\"none\" stroke=\"black\" d=\"M909,-816.884C909,-806.326 909,-794.597 909,-783.854\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"1055\" y=\"-758.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 31</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1055\" y=\"-743.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [31, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1055\" y=\"-728.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 24&#45;&gt;26 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"2057\" y=\"-1181.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 108.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2057\" y=\"-1166.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 1276</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2057\" y=\"-1151.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [1217, 59]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2057\" y=\"-1136.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 30&#45;&gt;31 -->\r\n",
       "<g id=\"edge31\" class=\"edge\"><title>30&#45;&gt;31</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2192.07,-1232.88C2172.58,-1222.95 2151.06,-1211.97 2131.03,-1201.76\"/>\r\n",
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       "<!-- 84 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"2610\" y=\"-1181.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">EmploymentStatus_Employed &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2610\" y=\"-1166.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 1347</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2610\" y=\"-1151.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [1205, 142]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2610\" y=\"-1136.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 30&#45;&gt;84 -->\r\n",
       "<g id=\"edge84\" class=\"edge\"><title>30&#45;&gt;84</title>\r\n",
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       "<!-- 32 -->\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.937255\" stroke=\"black\" points=\"1867.5,-1093 1664.5,-1093 1664.5,-1025 1867.5,-1025 1867.5,-1093\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1766\" y=\"-1077.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 105.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1766\" y=\"-1062.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 1006</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1766\" y=\"-1047.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [948, 58]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1766\" y=\"-1032.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 31&#45;&gt;32 -->\r\n",
       "<g id=\"edge32\" class=\"edge\"><title>31&#45;&gt;32</title>\r\n",
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       "<!-- 79 -->\r\n",
       "<g id=\"node80\" class=\"node\"><title>79</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.996078\" stroke=\"black\" points=\"2141,-1093 1973,-1093 1973,-1025 2141,-1025 2141,-1093\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2057\" y=\"-1077.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Coverage_Premium &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2057\" y=\"-1062.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 270</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2057\" y=\"-1047.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [269, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2057\" y=\"-1032.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 31&#45;&gt;79 -->\r\n",
       "<g id=\"edge79\" class=\"edge\"><title>31&#45;&gt;79</title>\r\n",
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       "<polygon fill=\"black\" stroke=\"black\" points=\"2060.5,-1103.3 2057,-1093.3 2053.5,-1103.3 2060.5,-1103.3\"/>\r\n",
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       "<!-- 33 -->\r\n",
       "<g id=\"node34\" class=\"node\"><title>33</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.949020\" stroke=\"black\" points=\"1632,-989 1408,-989 1408,-921 1632,-921 1632,-989\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1520\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 27659.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1520\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 945</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1520\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [898, 47]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1520\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 32&#45;&gt;33 -->\r\n",
       "<g id=\"edge33\" class=\"edge\"><title>32&#45;&gt;33</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1686.13,-1024.88C1661.62,-1014.72 1634.5,-1003.48 1609.4,-993.069\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1610.47,-989.722 1599.89,-989.125 1607.79,-996.188 1610.47,-989.722\"/>\r\n",
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       "<!-- 74 -->\r\n",
       "<g id=\"node75\" class=\"node\"><title>74</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.780392\" stroke=\"black\" points=\"1857.5,-989 1674.5,-989 1674.5,-921 1857.5,-921 1857.5,-989\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1766\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Sales Channel_Branch &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1766\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 61</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1766\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [50, 11]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1766\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 32&#45;&gt;74 -->\r\n",
       "<g id=\"edge74\" class=\"edge\"><title>32&#45;&gt;74</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1766,-1024.88C1766,-1016.78 1766,-1007.98 1766,-999.472\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1769.5,-999.299 1766,-989.299 1762.5,-999.299 1769.5,-999.299\"/>\r\n",
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       "<!-- 34 -->\r\n",
       "<g id=\"node35\" class=\"node\"><title>34</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.952941\" stroke=\"black\" points=\"1438,-885 1192,-885 1192,-817 1438,-817 1438,-885\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1315\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Education_High School or Below &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1315\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 928</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1315\" y=\"-839.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [885, 43]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1315\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 33&#45;&gt;34 -->\r\n",
       "<g id=\"edge34\" class=\"edge\"><title>33&#45;&gt;34</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1453.44,-920.884C1433.38,-910.901 1411.21,-899.872 1390.61,-889.619\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1392.09,-886.446 1381.57,-885.125 1388.97,-892.713 1392.09,-886.446\"/>\r\n",
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       "<!-- 73 -->\r\n",
       "<g id=\"node74\" class=\"node\"><title>73</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.694118\" stroke=\"black\" points=\"1584,-877.5 1456,-877.5 1456,-824.5 1584,-824.5 1584,-877.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1520\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 17</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1520\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [13, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1520\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 33&#45;&gt;73 -->\r\n",
       "<g id=\"edge73\" class=\"edge\"><title>33&#45;&gt;73</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1520,-920.884C1520,-910.326 1520,-898.597 1520,-887.854\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1523.5,-887.52 1520,-877.52 1516.5,-887.52 1523.5,-887.52\"/>\r\n",
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       "<!-- 35 -->\r\n",
       "<g id=\"node36\" class=\"node\"><title>35</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.937255\" stroke=\"black\" points=\"1403.5,-781 1166.5,-781 1166.5,-713 1403.5,-713 1403.5,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1285\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 93.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1285\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 749</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1285\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [706, 43]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1285\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 34&#45;&gt;35 -->\r\n",
       "<g id=\"edge35\" class=\"edge\"><title>34&#45;&gt;35</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1305.26,-816.884C1302.82,-808.6 1300.18,-799.595 1297.62,-790.911\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1300.97,-789.905 1294.79,-781.299 1294.26,-791.881 1300.97,-789.905\"/>\r\n",
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       "<!-- 72 -->\r\n",
       "<g id=\"node73\" class=\"node\"><title>72</title>\r\n",
       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"1550,-773.5 1422,-773.5 1422,-720.5 1550,-720.5 1550,-773.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1486\" y=\"-758.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 179</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1486\" y=\"-743.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [179, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1486\" y=\"-728.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 34&#45;&gt;72 -->\r\n",
       "<g id=\"edge72\" class=\"edge\"><title>34&#45;&gt;72</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1370.52,-816.884C1391.08,-804.621 1414.28,-790.779 1434.47,-778.737\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1436.42,-781.649 1443.22,-773.52 1432.84,-775.637 1436.42,-781.649\"/>\r\n",
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       "<!-- 36 -->\r\n",
       "<g id=\"node37\" class=\"node\"><title>36</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.945098\" stroke=\"black\" points=\"1396.5,-677 1159.5,-677 1159.5,-609 1396.5,-609 1396.5,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1278\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 3874.4053</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1278\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 713</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1278\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [676, 37]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1278\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 35&#45;&gt;36 -->\r\n",
       "<g id=\"edge36\" class=\"edge\"><title>35&#45;&gt;36</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1282.73,-712.884C1282.17,-704.778 1281.57,-695.982 1280.98,-687.472\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1284.46,-687.036 1280.29,-677.299 1277.48,-687.516 1284.46,-687.036\"/>\r\n",
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       "<!-- 69 -->\r\n",
       "<g id=\"node70\" class=\"node\"><title>69</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.800000\" stroke=\"black\" points=\"1543,-677 1415,-677 1415,-609 1543,-609 1543,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1479\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 61965.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1479\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 36</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1479\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [30, 6]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1479\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 35&#45;&gt;69 -->\r\n",
       "<g id=\"edge69\" class=\"edge\"><title>35&#45;&gt;69</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1347.99,-712.884C1366.8,-702.991 1387.57,-692.07 1406.92,-681.895\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1408.78,-684.876 1416,-677.125 1405.52,-678.681 1408.78,-684.876\"/>\r\n",
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       "<!-- 37 -->\r\n",
       "<g id=\"node38\" class=\"node\"><title>37</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.905882\" stroke=\"black\" points=\"1080.5,-573 843.5,-573 843.5,-505 1080.5,-505 1080.5,-573\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"962\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 3226.9541</text>\r\n",
       "<text text-anchor=\"middle\" x=\"962\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 240</text>\r\n",
       "<text text-anchor=\"middle\" x=\"962\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [219, 21]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"962\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 36&#45;&gt;37 -->\r\n",
       "<g id=\"edge37\" class=\"edge\"><title>36&#45;&gt;37</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1175.4,-608.884C1143.01,-598.427 1107.06,-586.822 1074.04,-576.164\"/>\r\n",
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       "<!-- 52 -->\r\n",
       "<g id=\"node53\" class=\"node\"><title>52</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.964706\" stroke=\"black\" points=\"1382,-573 1186,-573 1186,-505 1382,-505 1382,-573\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1284\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 66.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1284\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 473</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1284\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [457, 16]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1284\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 36&#45;&gt;52 -->\r\n",
       "<g id=\"edge52\" class=\"edge\"><title>36&#45;&gt;52</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1279.95,-608.884C1280.42,-600.778 1280.94,-591.982 1281.44,-583.472\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1284.95,-583.488 1282.04,-573.299 1277.96,-583.077 1284.95,-583.488\"/>\r\n",
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       "<!-- 38 -->\r\n",
       "<g id=\"node39\" class=\"node\"><title>38</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.956863\" stroke=\"black\" points=\"809,-469 639,-469 639,-401 809,-401 809,-469\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"724\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Sales Channel_Web &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"724\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 168</text>\r\n",
       "<text text-anchor=\"middle\" x=\"724\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [161, 7]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"724\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 37&#45;&gt;38 -->\r\n",
       "<g id=\"edge38\" class=\"edge\"><title>37&#45;&gt;38</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M884.728,-504.884C861.018,-494.722 834.778,-483.476 810.493,-473.069\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"811.861,-469.847 801.291,-469.125 809.104,-476.281 811.861,-469.847\"/>\r\n",
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       "<g id=\"node46\" class=\"node\"><title>45</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.756863\" stroke=\"black\" points=\"1061.5,-469 862.5,-469 862.5,-401 1061.5,-401 1061.5,-469\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"962\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 4.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"962\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 72</text>\r\n",
       "<text text-anchor=\"middle\" x=\"962\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [58, 14]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"962\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 37&#45;&gt;45 -->\r\n",
       "<g id=\"edge45\" class=\"edge\"><title>37&#45;&gt;45</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M962,-504.884C962,-496.778 962,-487.982 962,-479.472\"/>\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"626,-357.5 498,-357.5 498,-304.5 626,-304.5 626,-357.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"562\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 115</text>\r\n",
       "<text text-anchor=\"middle\" x=\"562\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [115, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"562\" y=\"-312.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 38&#45;&gt;39 -->\r\n",
       "<g id=\"edge39\" class=\"edge\"><title>38&#45;&gt;39</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M671.403,-400.884C652.015,-388.676 630.14,-374.903 611.075,-362.899\"/>\r\n",
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       "<!-- 40 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"724\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Education_Master &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"724\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 53</text>\r\n",
       "<text text-anchor=\"middle\" x=\"724\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [46, 7]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"724\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 38&#45;&gt;40 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"586\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 72066.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"586\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 38</text>\r\n",
       "<text text-anchor=\"middle\" x=\"586\" y=\"-215.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [36, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"586\" y=\"-200.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 40&#45;&gt;41 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"732\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"732\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [10, 5]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"732\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 40&#45;&gt;44 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"513\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 23</text>\r\n",
       "<text text-anchor=\"middle\" x=\"513\" y=\"-119.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [23, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"513\" y=\"-104.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 41&#45;&gt;42 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"659\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"659\" y=\"-119.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [13, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"659\" y=\"-104.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 41&#45;&gt;43 -->\r\n",
       "<g id=\"edge43\" class=\"edge\"><title>41&#45;&gt;43</title>\r\n",
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       "<g id=\"node47\" class=\"node\"><title>46</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"886\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 19</text>\r\n",
       "<text text-anchor=\"middle\" x=\"886\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [10, 9]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"886\" y=\"-312.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 45&#45;&gt;46 -->\r\n",
       "<g id=\"edge46\" class=\"edge\"><title>45&#45;&gt;46</title>\r\n",
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       "<g id=\"node48\" class=\"node\"><title>47</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.894118\" stroke=\"black\" points=\"1096,-365 968,-365 968,-297 1096,-297 1096,-365\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1032\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 34646.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1032\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 53</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1032\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [48, 5]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1032\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 45&#45;&gt;47 -->\r\n",
       "<g id=\"edge47\" class=\"edge\"><title>45&#45;&gt;47</title>\r\n",
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       "<!-- 48 -->\r\n",
       "<g id=\"node49\" class=\"node\"><title>48</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.635294\" stroke=\"black\" points=\"950,-253.5 822,-253.5 822,-200.5 950,-200.5 950,-253.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"886\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"886\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [11, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"886\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 47&#45;&gt;48 -->\r\n",
       "<g id=\"edge48\" class=\"edge\"><title>47&#45;&gt;48</title>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.972549\" stroke=\"black\" points=\"1096,-261 968,-261 968,-193 1096,-193 1096,-261\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1032\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 59038.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1032\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 38</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1032\" y=\"-215.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [37, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1032\" y=\"-200.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 47&#45;&gt;49 -->\r\n",
       "<g id=\"edge49\" class=\"edge\"><title>47&#45;&gt;49</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1032,-296.884C1032,-288.778 1032,-279.982 1032,-271.472\"/>\r\n",
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       "<g id=\"node51\" class=\"node\"><title>50</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.929412\" stroke=\"black\" points=\"1021,-149.5 893,-149.5 893,-96.5 1021,-96.5 1021,-149.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"957\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"957\" y=\"-119.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"957\" y=\"-104.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 49&#45;&gt;50 -->\r\n",
       "<g id=\"edge50\" class=\"edge\"><title>49&#45;&gt;50</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1007.65,-192.884C999.401,-181.666 990.181,-169.126 981.891,-157.852\"/>\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"1167,-149.5 1039,-149.5 1039,-96.5 1167,-96.5 1167,-149.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1103\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 23</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1103\" y=\"-119.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [23, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1103\" y=\"-104.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 49&#45;&gt;51 -->\r\n",
       "<g id=\"edge51\" class=\"edge\"><title>49&#45;&gt;51</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1055.05,-192.884C1062.86,-181.666 1071.59,-169.126 1079.44,-157.852\"/>\r\n",
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       "<g id=\"node54\" class=\"node\"><title>53</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"1284\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 30.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1284\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 130</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1284\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [118, 12]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1284\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 52&#45;&gt;53 -->\r\n",
       "<g id=\"edge53\" class=\"edge\"><title>52&#45;&gt;53</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1284,-504.884C1284,-496.778 1284,-487.982 1284,-479.472\"/>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.988235\" stroke=\"black\" points=\"1756,-469 1550,-469 1550,-401 1756,-401 1756,-469\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1653\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 29.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1653\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 343</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1653\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [339, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1653\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 52&#45;&gt;60 -->\r\n",
       "<g id=\"edge60\" class=\"edge\"><title>52&#45;&gt;60</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1382.3,-508.891C1386.93,-507.566 1391.51,-506.263 1396,-505 1443.13,-491.733 1495.28,-477.626 1540.21,-465.648\"/>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.725490\" stroke=\"black\" points=\"1385.5,-365 1148.5,-365 1148.5,-297 1385.5,-297 1385.5,-365\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1267\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 5211.8154</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1267\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 56</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1267\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [44, 12]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1267\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 53&#45;&gt;54 -->\r\n",
       "<g id=\"edge54\" class=\"edge\"><title>53&#45;&gt;54</title>\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"1532,-357.5 1404,-357.5 1404,-304.5 1532,-304.5 1532,-357.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1468\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 74</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1468\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [74, 0]</text>\r\n",
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       "<!-- 53&#45;&gt;59 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"1178\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 18</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1178\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [18, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1178\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 54&#45;&gt;55 -->\r\n",
       "<g id=\"edge55\" class=\"edge\"><title>54&#45;&gt;55</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"1379\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 7604.8872</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1379\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 38</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1379\" y=\"-215.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [26, 12]</text>\r\n",
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       "<!-- 54&#45;&gt;56 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"1320\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 18</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"1653\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 88945.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1653\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 296</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"1872\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 91.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1872\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 47</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"1726\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 91141.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1726\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 41</text>\r\n",
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       "<!-- 61&#45;&gt;63 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"1639\" y=\"-104.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 63&#45;&gt;64 -->\r\n",
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       "<!-- 63&#45;&gt;65 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"1872\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 32</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"1872\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 66&#45;&gt;67 -->\r\n",
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       "<g id=\"node69\" class=\"node\"><title>68</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.749020\" stroke=\"black\" points=\"2082,-253.5 1954,-253.5 1954,-200.5 2082,-200.5 2082,-253.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2018\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2018\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [12, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2018\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 66&#45;&gt;68 -->\r\n",
       "<g id=\"edge68\" class=\"edge\"><title>66&#45;&gt;68</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1919.4,-296.884C1936.56,-284.896 1955.88,-271.399 1972.84,-259.549\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"1975.28,-262.116 1981.47,-253.52 1971.27,-256.378 1975.28,-262.116\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"1469\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 18</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1469\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [18, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1469\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 69&#45;&gt;70 -->\r\n",
       "<g id=\"edge70\" class=\"edge\"><title>69&#45;&gt;70</title>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.498039\" stroke=\"black\" points=\"1679,-565.5 1551,-565.5 1551,-512.5 1679,-512.5 1679,-565.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"1615\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 18</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1615\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [12, 6]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1615\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 69&#45;&gt;71 -->\r\n",
       "<g id=\"edge71\" class=\"edge\"><title>69&#45;&gt;71</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1523.16,-608.884C1539.14,-596.896 1557.13,-583.399 1572.93,-571.549\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"1666\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 25</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1666\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [25, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1666\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 74&#45;&gt;75 -->\r\n",
       "<g id=\"edge75\" class=\"edge\"><title>74&#45;&gt;75</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1733.53,-920.884C1722.21,-909.336 1709.52,-896.387 1698.22,-884.86\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"1867\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 8593.7617</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1867\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 36</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"1867\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 74&#45;&gt;76 -->\r\n",
       "<g id=\"edge76\" class=\"edge\"><title>74&#45;&gt;76</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"1794\" y=\"-758.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 20</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"1794\" y=\"-728.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 76&#45;&gt;77 -->\r\n",
       "<g id=\"edge77\" class=\"edge\"><title>76&#45;&gt;77</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M1843.3,-816.884C1835.27,-805.666 1826.3,-793.126 1818.23,-781.852\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"1940\" y=\"-758.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 16</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"1940\" y=\"-728.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 76&#45;&gt;78 -->\r\n",
       "<g id=\"edge78\" class=\"edge\"><title>76&#45;&gt;78</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"1987\" y=\"-966.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 213</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1987\" y=\"-951.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [213, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"1987\" y=\"-936.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 79&#45;&gt;80 -->\r\n",
       "<g id=\"edge80\" class=\"edge\"><title>79&#45;&gt;80</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"2191\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 13901.3633</text>\r\n",
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       "<g id=\"edge81\" class=\"edge\"><title>79&#45;&gt;81</title>\r\n",
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       "<!-- 82 -->\r\n",
       "<g id=\"node83\" class=\"node\"><title>82</title>\r\n",
       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"2132,-877.5 2004,-877.5 2004,-824.5 2132,-824.5 2132,-877.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2068\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 42</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2068\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [42, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2068\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 81&#45;&gt;82 -->\r\n",
       "<g id=\"edge82\" class=\"edge\"><title>81&#45;&gt;82</title>\r\n",
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       "<!-- 83 -->\r\n",
       "<g id=\"node84\" class=\"node\"><title>83</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.929412\" stroke=\"black\" points=\"2278,-877.5 2150,-877.5 2150,-824.5 2278,-824.5 2278,-877.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2214\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2214\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2214\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 81&#45;&gt;83 -->\r\n",
       "<g id=\"edge83\" class=\"edge\"><title>81&#45;&gt;83</title>\r\n",
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       "<!-- 85 -->\r\n",
       "<g id=\"node86\" class=\"node\"><title>85</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.796078\" stroke=\"black\" points=\"2684.5,-1093 2535.5,-1093 2535.5,-1025 2684.5,-1025 2684.5,-1093\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2610\" y=\"-1077.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Coverage_Basic &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2610\" y=\"-1062.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 277</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2610\" y=\"-1047.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [230, 47]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2610\" y=\"-1032.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 84&#45;&gt;85 -->\r\n",
       "<g id=\"edge85\" class=\"edge\"><title>84&#45;&gt;85</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2610,-1128.88C2610,-1120.78 2610,-1111.98 2610,-1103.47\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2613.5,-1103.3 2610,-1093.3 2606.5,-1103.3 2613.5,-1103.3\"/>\r\n",
       "</g>\r\n",
       "<!-- 102 -->\r\n",
       "<g id=\"node103\" class=\"node\"><title>102</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.901961\" stroke=\"black\" points=\"3379.5,-1093 3176.5,-1093 3176.5,-1025 3379.5,-1025 3379.5,-1093\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3278\" y=\"-1077.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 102.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3278\" y=\"-1062.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 1070</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3278\" y=\"-1047.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [975, 95]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3278\" y=\"-1032.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 84&#45;&gt;102 -->\r\n",
       "<g id=\"edge102\" class=\"edge\"><title>84&#45;&gt;102</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2723.7,-1144.64C2847.22,-1125.78 3043.32,-1095.83 3166.13,-1077.08\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"3166.95,-1080.5 3176.31,-1075.53 3165.9,-1073.58 3166.95,-1080.5\"/>\r\n",
       "</g>\r\n",
       "<!-- 86 -->\r\n",
       "<g id=\"node87\" class=\"node\"><title>86</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.976471\" stroke=\"black\" points=\"2608.5,-989 2371.5,-989 2371.5,-921 2608.5,-921 2608.5,-989\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2490\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 78.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2490\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 84</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2490\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [82, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2490\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 85&#45;&gt;86 -->\r\n",
       "<g id=\"edge86\" class=\"edge\"><title>85&#45;&gt;86</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2571.04,-1024.88C2560.14,-1015.62 2548.18,-1005.45 2536.88,-995.845\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2539.06,-993.109 2529.18,-989.299 2534.53,-998.443 2539.06,-993.109\"/>\r\n",
       "</g>\r\n",
       "<!-- 89 -->\r\n",
       "<g id=\"node90\" class=\"node\"><title>89</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.694118\" stroke=\"black\" points=\"2833,-989 2627,-989 2627,-921 2833,-921 2833,-989\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2730\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 10.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2730\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 193</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2730\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [148, 45]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2730\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 85&#45;&gt;89 -->\r\n",
       "<g id=\"edge89\" class=\"edge\"><title>85&#45;&gt;89</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2648.96,-1024.88C2659.86,-1015.62 2671.82,-1005.45 2683.12,-995.845\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2685.47,-998.443 2690.82,-989.299 2680.94,-993.109 2685.47,-998.443\"/>\r\n",
       "</g>\r\n",
       "<!-- 87 -->\r\n",
       "<g id=\"node88\" class=\"node\"><title>87</title>\r\n",
       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"2424,-877.5 2296,-877.5 2296,-824.5 2424,-824.5 2424,-877.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2360\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 69</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2360\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [69, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2360\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 86&#45;&gt;87 -->\r\n",
       "<g id=\"edge87\" class=\"edge\"><title>86&#45;&gt;87</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2447.79,-920.884C2432.65,-909.006 2415.63,-895.646 2400.63,-883.876\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2402.55,-880.939 2392.53,-877.52 2398.23,-886.446 2402.55,-880.939\"/>\r\n",
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       "<!-- 88 -->\r\n",
       "<g id=\"node89\" class=\"node\"><title>88</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.847059\" stroke=\"black\" points=\"2570,-877.5 2442,-877.5 2442,-824.5 2570,-824.5 2570,-877.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2506\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2506\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [13, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2506\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 86&#45;&gt;88 -->\r\n",
       "<g id=\"edge88\" class=\"edge\"><title>86&#45;&gt;88</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2495.19,-920.884C2496.87,-910.216 2498.73,-898.352 2500.43,-887.519\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2503.9,-887.942 2502,-877.52 2496.99,-886.857 2503.9,-887.942\"/>\r\n",
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       "<!-- 90 -->\r\n",
       "<g id=\"node91\" class=\"node\"><title>90</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.356863\" stroke=\"black\" points=\"2825.5,-885 2588.5,-885 2588.5,-817 2825.5,-817 2825.5,-885\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2707\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 7678.6211</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2707\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 74</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2707\" y=\"-839.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [45, 29]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2707\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 89&#45;&gt;90 -->\r\n",
       "<g id=\"edge90\" class=\"edge\"><title>89&#45;&gt;90</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2722.53,-920.884C2720.68,-912.689 2718.68,-903.789 2716.74,-895.192\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2720.12,-894.285 2714.51,-885.299 2713.29,-895.824 2720.12,-894.285\"/>\r\n",
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       "<!-- 95 -->\r\n",
       "<g id=\"node96\" class=\"node\"><title>95</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.843137\" stroke=\"black\" points=\"2972,-885 2844,-885 2844,-817 2972,-817 2972,-885\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2908\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 22582.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2908\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 119</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2908\" y=\"-839.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [103, 16]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2908\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 89&#45;&gt;95 -->\r\n",
       "<g id=\"edge95\" class=\"edge\"><title>89&#45;&gt;95</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2787.79,-920.884C2804.82,-911.125 2823.6,-900.366 2841.14,-890.31\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2843.26,-893.133 2850.19,-885.125 2839.78,-887.06 2843.26,-893.133\"/>\r\n",
       "</g>\r\n",
       "<!-- 91 -->\r\n",
       "<g id=\"node92\" class=\"node\"><title>91</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.713725\" stroke=\"black\" points=\"2537.5,-781 2300.5,-781 2300.5,-713 2537.5,-713 2537.5,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2419\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 52.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2419\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 45</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2419\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [35, 10]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2419\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 90&#45;&gt;91 -->\r\n",
       "<g id=\"edge91\" class=\"edge\"><title>90&#45;&gt;91</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2613.49,-816.884C2584.3,-806.543 2551.93,-795.079 2522.11,-784.519\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2523.12,-781.164 2512.53,-781.125 2520.79,-787.762 2523.12,-781.164\"/>\r\n",
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       "<!-- 94 -->\r\n",
       "<g id=\"node95\" class=\"node\"><title>94</title>\r\n",
       "<polygon fill=\"#399de5\" fill-opacity=\"0.474510\" stroke=\"black\" points=\"2666,-773.5 2556,-773.5 2556,-720.5 2666,-720.5 2666,-773.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2611\" y=\"-758.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 29</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2611\" y=\"-743.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [10, 19]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2611\" y=\"-728.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 90&#45;&gt;94 -->\r\n",
       "<g id=\"edge94\" class=\"edge\"><title>90&#45;&gt;94</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2675.83,-816.884C2664.96,-805.336 2652.78,-792.387 2641.93,-780.86\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2644.42,-778.403 2635.02,-773.52 2639.32,-783.201 2644.42,-778.403\"/>\r\n",
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       "<!-- 92 -->\r\n",
       "<g id=\"node93\" class=\"node\"><title>92</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.376471\" stroke=\"black\" points=\"2400,-669.5 2272,-669.5 2272,-616.5 2400,-616.5 2400,-669.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2336\" y=\"-654.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 26</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2336\" y=\"-639.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [16, 10]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2336\" y=\"-624.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 91&#45;&gt;92 -->\r\n",
       "<g id=\"edge92\" class=\"edge\"><title>91&#45;&gt;92</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2392.05,-712.884C2382.83,-701.556 2372.52,-688.88 2363.28,-677.521\"/>\r\n",
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       "<g id=\"node94\" class=\"node\"><title>93</title>\r\n",
       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"2546,-669.5 2418,-669.5 2418,-616.5 2546,-616.5 2546,-669.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2482\" y=\"-654.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 19</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2482\" y=\"-639.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [19, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2482\" y=\"-624.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 91&#45;&gt;93 -->\r\n",
       "<g id=\"edge93\" class=\"edge\"><title>91&#45;&gt;93</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2439.45,-712.884C2446.32,-701.776 2453.98,-689.372 2460.89,-678.184\"/>\r\n",
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       "<g id=\"node97\" class=\"node\"><title>96</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.713725\" stroke=\"black\" points=\"2921.5,-781 2684.5,-781 2684.5,-713 2921.5,-713 2921.5,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2803\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 5516.7554</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2803\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 72</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2803\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [56, 16]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2803\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 95&#45;&gt;96 -->\r\n",
       "<g id=\"edge96\" class=\"edge\"><title>95&#45;&gt;96</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2873.91,-816.884C2864.56,-807.798 2854.31,-797.845 2844.59,-788.4\"/>\r\n",
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       "<!-- 101 -->\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"3068,-773.5 2940,-773.5 2940,-720.5 3068,-720.5 3068,-773.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3004\" y=\"-758.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 47</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3004\" y=\"-743.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [47, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3004\" y=\"-728.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 95&#45;&gt;101 -->\r\n",
       "<g id=\"edge101\" class=\"edge\"><title>95&#45;&gt;101</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2939.17,-816.884C2950.04,-805.336 2962.22,-792.387 2973.07,-780.86\"/>\r\n",
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       "<g id=\"node98\" class=\"node\"><title>97</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.466667\" stroke=\"black\" points=\"2738,-677 2610,-677 2610,-609 2738,-609 2738,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2674\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 19789.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2674\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 46</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2674\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [30, 16]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2674\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 96&#45;&gt;97 -->\r\n",
       "<g id=\"edge97\" class=\"edge\"><title>96&#45;&gt;97</title>\r\n",
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       "<!-- 100 -->\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"2884,-669.5 2756,-669.5 2756,-616.5 2884,-616.5 2884,-669.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2820\" y=\"-654.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 26</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2820\" y=\"-639.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [26, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2820\" y=\"-624.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 96&#45;&gt;100 -->\r\n",
       "<g id=\"edge100\" class=\"edge\"><title>96&#45;&gt;100</title>\r\n",
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       "<!-- 98 -->\r\n",
       "<g id=\"node99\" class=\"node\"><title>98</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.784314\" stroke=\"black\" points=\"2626,-565.5 2498,-565.5 2498,-512.5 2626,-512.5 2626,-565.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2562\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 28</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2562\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [23, 5]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2562\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 97&#45;&gt;98 -->\r\n",
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       "<!-- 99 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"2699\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 18</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2699\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [7, 11]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2699\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 97&#45;&gt;99 -->\r\n",
       "<g id=\"edge99\" class=\"edge\"><title>97&#45;&gt;99</title>\r\n",
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       "<!-- 103 -->\r\n",
       "<g id=\"node104\" class=\"node\"><title>103</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.933333\" stroke=\"black\" points=\"3342,-989 3214,-989 3214,-921 3342,-921 3342,-989\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3278\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 21605.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3278\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 671</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3278\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [629, 42]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3278\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 102&#45;&gt;103 -->\r\n",
       "<g id=\"edge103\" class=\"edge\"><title>102&#45;&gt;103</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3278,-1024.88C3278,-1016.78 3278,-1007.98 3278,-999.472\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"3281.5,-999.299 3278,-989.299 3274.5,-999.299 3281.5,-999.299\"/>\r\n",
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       "<!-- 138 -->\r\n",
       "<g id=\"node139\" class=\"node\"><title>138</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.847059\" stroke=\"black\" points=\"3920.5,-989 3683.5,-989 3683.5,-921 3920.5,-921 3920.5,-989\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3802\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 17.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3802\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 399</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3802\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [346, 53]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3802\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 102&#45;&gt;138 -->\r\n",
       "<g id=\"edge138\" class=\"edge\"><title>102&#45;&gt;138</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3379.65,-1038.21C3463.42,-1021.91 3582.71,-998.685 3673.17,-981.078\"/>\r\n",
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       "<!-- 104 -->\r\n",
       "<g id=\"node105\" class=\"node\"><title>104</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.643137\" stroke=\"black\" points=\"3244,-877.5 3116,-877.5 3116,-824.5 3244,-824.5 3244,-877.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3180\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 19</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3180\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 5]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3180\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 103&#45;&gt;104 -->\r\n",
       "<g id=\"edge104\" class=\"edge\"><title>103&#45;&gt;104</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3246.18,-920.884C3235.09,-909.336 3222.65,-896.387 3211.57,-884.86\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"3213.97,-882.306 3204.52,-877.52 3208.92,-887.156 3213.97,-882.306\"/>\r\n",
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       "<!-- 105 -->\r\n",
       "<g id=\"node106\" class=\"node\"><title>105</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.941176\" stroke=\"black\" points=\"3492,-885 3262,-885 3262,-817 3492,-817 3492,-885\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3377\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 3.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3377\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 652</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3377\" y=\"-839.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [615, 37]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3377\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 103&#45;&gt;105 -->\r\n",
       "<g id=\"edge105\" class=\"edge\"><title>103&#45;&gt;105</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3310.14,-920.884C3318.87,-911.887 3328.43,-902.041 3337.52,-892.678\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"3340.23,-894.913 3344.68,-885.299 3335.2,-890.038 3340.23,-894.913\"/>\r\n",
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       "<!-- 106 -->\r\n",
       "<g id=\"node107\" class=\"node\"><title>106</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.776471\" stroke=\"black\" points=\"3323.5,-781 3086.5,-781 3086.5,-713 3323.5,-713 3323.5,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3205\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 7611.0176</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3205\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 49</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3205\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [40, 9]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3205\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 105&#45;&gt;106 -->\r\n",
       "<g id=\"edge106\" class=\"edge\"><title>105&#45;&gt;106</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3321.16,-816.884C3304.7,-807.125 3286.56,-796.366 3269.6,-786.31\"/>\r\n",
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       "<!-- 111 -->\r\n",
       "<g id=\"node112\" class=\"node\"><title>111</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.952941\" stroke=\"black\" points=\"3470,-781 3342,-781 3342,-713 3470,-713 3470,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3406\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Gender_M &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3406\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 603</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3406\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [575, 28]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3406\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 105&#45;&gt;111 -->\r\n",
       "<g id=\"edge111\" class=\"edge\"><title>105&#45;&gt;111</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3386.42,-816.884C3388.75,-808.689 3391.28,-799.789 3393.72,-791.192\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"3397.16,-791.875 3396.53,-781.299 3390.43,-789.961 3397.16,-791.875\"/>\r\n",
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       "<!-- 107 -->\r\n",
       "<g id=\"node108\" class=\"node\"><title>107</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.901961\" stroke=\"black\" points=\"3090,-677 2924,-677 2924,-609 3090,-609 3090,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3007\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Number of Policies &lt;= 5.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3007\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 34</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3007\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [31, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3007\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 106&#45;&gt;107 -->\r\n",
       "<g id=\"edge107\" class=\"edge\"><title>106&#45;&gt;107</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3140.72,-712.884C3121.42,-702.946 3100.12,-691.971 3080.29,-681.757\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"3081.79,-678.593 3071.3,-677.125 3078.59,-684.816 3081.79,-678.593\"/>\r\n",
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       "<!-- 110 -->\r\n",
       "<g id=\"node111\" class=\"node\"><title>110</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.333333\" stroke=\"black\" points=\"3252,-669.5 3124,-669.5 3124,-616.5 3252,-616.5 3252,-669.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3188\" y=\"-654.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3188\" y=\"-639.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [9, 6]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3188\" y=\"-624.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 106&#45;&gt;110 -->\r\n",
       "<g id=\"edge110\" class=\"edge\"><title>106&#45;&gt;110</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3199.48,-712.884C3197.7,-702.216 3195.73,-690.352 3193.92,-679.519\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"3197.35,-678.808 3192.25,-669.52 3190.45,-679.959 3197.35,-678.808\"/>\r\n",
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       "<!-- 108 -->\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"2925,-565.5 2797,-565.5 2797,-512.5 2925,-512.5 2925,-565.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"2861\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 17</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2861\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [17, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"2861\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 107&#45;&gt;108 -->\r\n",
       "<g id=\"edge108\" class=\"edge\"><title>107&#45;&gt;108</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M2959.6,-608.884C2942.44,-596.896 2923.12,-583.399 2906.16,-571.549\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"2907.73,-568.378 2897.53,-565.52 2903.72,-574.116 2907.73,-568.378\"/>\r\n",
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       "<!-- 109 -->\r\n",
       "<g id=\"node110\" class=\"node\"><title>109</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.784314\" stroke=\"black\" points=\"3071,-565.5 2943,-565.5 2943,-512.5 3071,-512.5 3071,-565.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3007\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 17</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3007\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3007\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 107&#45;&gt;109 -->\r\n",
       "<g id=\"edge109\" class=\"edge\"><title>107&#45;&gt;109</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3007,-608.884C3007,-598.326 3007,-586.597 3007,-575.854\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"3010.5,-575.52 3007,-565.52 3003.5,-575.52 3010.5,-575.52\"/>\r\n",
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       "<!-- 112 -->\r\n",
       "<g id=\"node113\" class=\"node\"><title>112</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.988235\" stroke=\"black\" points=\"3430,-677 3270,-677 3270,-609 3430,-609 3430,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3350\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Marital Status_Sin &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3350\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 262</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3350\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [259, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3350\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 111&#45;&gt;112 -->\r\n",
       "<g id=\"edge112\" class=\"edge\"><title>111&#45;&gt;112</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3387.82,-712.884C3383.12,-704.332 3378.01,-695.013 3373.1,-686.072\"/>\r\n",
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       "<!-- 117 -->\r\n",
       "<g id=\"node118\" class=\"node\"><title>117</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.921569\" stroke=\"black\" points=\"3696.5,-677 3459.5,-677 3459.5,-609 3696.5,-609 3696.5,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3578\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 88.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3578\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 341</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3578\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [316, 25]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3578\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 111&#45;&gt;117 -->\r\n",
       "<g id=\"edge117\" class=\"edge\"><title>111&#45;&gt;117</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3461.84,-712.884C3478.3,-703.125 3496.44,-692.366 3513.4,-682.31\"/>\r\n",
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       "<!-- 113 -->\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"3217,-565.5 3089,-565.5 3089,-512.5 3217,-512.5 3217,-565.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3153\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 227</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3153\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [227, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3153\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 112&#45;&gt;113 -->\r\n",
       "<g id=\"edge113\" class=\"edge\"><title>112&#45;&gt;113</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3286.04,-608.884C3262.04,-596.456 3234.9,-582.406 3211.43,-570.252\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"3212.78,-567.01 3202.29,-565.52 3209.56,-573.226 3212.78,-567.01\"/>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.905882\" stroke=\"black\" points=\"3441,-573 3235,-573 3235,-505 3441,-505 3441,-573\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3338\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 21.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3338\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 35</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3338\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [32, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3338\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 112&#45;&gt;114 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"3155\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 20</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3155\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [20, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3155\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 114&#45;&gt;115 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"3301\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3301\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [12, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3301\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 114&#45;&gt;116 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"3578\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 37.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3578\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 310</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3578\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [292, 18]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3578\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 117&#45;&gt;118 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"3833\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 5068.3848</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3833\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 31</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3833\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [24, 7]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3833\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 117&#45;&gt;135 -->\r\n",
       "<g id=\"edge135\" class=\"edge\"><title>117&#45;&gt;135</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"3447\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 55695.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3447\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 127</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3447\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [125, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3447\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 118&#45;&gt;119 -->\r\n",
       "<g id=\"edge119\" class=\"edge\"><title>118&#45;&gt;119</title>\r\n",
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       "<g id=\"node125\" class=\"node\"><title>124</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.905882\" stroke=\"black\" points=\"3766.5,-469 3529.5,-469 3529.5,-401 3766.5,-401 3766.5,-469\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3648\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 72.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3648\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 183</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3648\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [167, 16]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3648\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 118&#45;&gt;124 -->\r\n",
       "<g id=\"edge124\" class=\"edge\"><title>118&#45;&gt;124</title>\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"3314,-357.5 3186,-357.5 3186,-304.5 3314,-304.5 3314,-357.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3250\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 78</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3250\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [78, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3250\" y=\"-312.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 119&#45;&gt;120 -->\r\n",
       "<g id=\"edge120\" class=\"edge\"><title>119&#45;&gt;120</title>\r\n",
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       "<g id=\"node122\" class=\"node\"><title>121</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.956863\" stroke=\"black\" points=\"3528,-365 3332,-365 3332,-297 3528,-297 3528,-365\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3430\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 68.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3430\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 49</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3430\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [47, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3430\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 119&#45;&gt;121 -->\r\n",
       "<g id=\"edge121\" class=\"edge\"><title>119&#45;&gt;121</title>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.874510\" stroke=\"black\" points=\"3370,-253.5 3242,-253.5 3242,-200.5 3370,-200.5 3370,-253.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3306\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 18</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3306\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [16, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3306\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 121&#45;&gt;122 -->\r\n",
       "<g id=\"edge122\" class=\"edge\"><title>121&#45;&gt;122</title>\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"3516,-253.5 3388,-253.5 3388,-200.5 3516,-200.5 3516,-253.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3452\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 31</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3452\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [31, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3452\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 121&#45;&gt;123 -->\r\n",
       "<g id=\"edge123\" class=\"edge\"><title>121&#45;&gt;123</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3437.14,-296.884C3439.44,-286.216 3442,-274.352 3444.34,-263.519\"/>\r\n",
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       "<!-- 125 -->\r\n",
       "<g id=\"node126\" class=\"node\"><title>125</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.862745\" stroke=\"black\" points=\"3783.5,-365 3546.5,-365 3546.5,-297 3783.5,-297 3783.5,-365\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3665\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 66.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3665\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 132</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3665\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [116, 16]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3665\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 124&#45;&gt;125 -->\r\n",
       "<g id=\"edge125\" class=\"edge\"><title>124&#45;&gt;125</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3653.52,-400.884C3654.89,-392.689 3656.37,-383.789 3657.8,-375.192\"/>\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"3930,-357.5 3802,-357.5 3802,-304.5 3930,-304.5 3930,-357.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3866\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 51</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3866\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [51, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3866\" y=\"-312.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 124&#45;&gt;134 -->\r\n",
       "<g id=\"edge134\" class=\"edge\"><title>124&#45;&gt;134</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3718.78,-400.884C3745.69,-388.291 3776.17,-374.033 3802.38,-361.769\"/>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.913725\" stroke=\"black\" points=\"3685,-261 3557,-261 3557,-193 3685,-193 3685,-261\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"3621\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 26024.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3621\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 101</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3621\" y=\"-215.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [93, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3621\" y=\"-200.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 125&#45;&gt;126 -->\r\n",
       "<g id=\"edge126\" class=\"edge\"><title>125&#45;&gt;126</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3650.71,-296.884C3647.1,-288.511 3643.17,-279.401 3639.39,-270.631\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"3822\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Sales Channel_Branch &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3822\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 31</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3822\" y=\"-215.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [23, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3822\" y=\"-200.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 125&#45;&gt;131 -->\r\n",
       "<g id=\"edge131\" class=\"edge\"><title>125&#45;&gt;131</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"3420\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 16</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3420\" y=\"-119.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [12, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3420\" y=\"-104.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 126&#45;&gt;127 -->\r\n",
       "<g id=\"edge127\" class=\"edge\"><title>126&#45;&gt;127</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"3621\" y=\"-141.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 55.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3621\" y=\"-126.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 85</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3621\" y=\"-111.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [81, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3621\" y=\"-96.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 126&#45;&gt;128 -->\r\n",
       "<g id=\"edge128\" class=\"edge\"><title>126&#45;&gt;128</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M3621,-192.884C3621,-184.778 3621,-175.982 3621,-167.472\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"3802\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [78, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"3802\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 138&#45;&gt;139 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"4253\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 6330.3125</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4253\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 321</text>\r\n",
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       "<!-- 138&#45;&gt;140 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"4253\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Coverage_Basic &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4253\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 107</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4253\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [79, 28]</text>\r\n",
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       "<!-- 140&#45;&gt;141 -->\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.866667\" stroke=\"black\" points=\"4752,-781 4586,-781 4586,-713 4752,-713 4752,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Number of Policies &lt;= 7.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 214</text>\r\n",
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       "<!-- 140&#45;&gt;150 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"4171\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 55057.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4171\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 59</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"4335\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Marital Status_Mar &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4335\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 48</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"4180\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 65166.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4180\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 35</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"4472\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 28</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4472\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [28, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4472\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 147&#45;&gt;149 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"4669\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 58.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 192</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [174, 18]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 150&#45;&gt;151 -->\r\n",
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       "<!-- 160 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"4870\" y=\"-654.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 22</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4870\" y=\"-639.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [15, 7]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4870\" y=\"-624.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 150&#45;&gt;160 -->\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.976471\" stroke=\"black\" points=\"4784,-573 4554,-573 4554,-505 4784,-505 4784,-573\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 9136.502</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 94</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [92, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 151&#45;&gt;152 -->\r\n",
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       "<!-- 155 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"4921\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 61.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4921\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 98</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4921\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [82, 16]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4921\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 151&#45;&gt;155 -->\r\n",
       "<g id=\"edge155\" class=\"edge\"><title>151&#45;&gt;155</title>\r\n",
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       "<!-- 153 -->\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.925490\" stroke=\"black\" points=\"4587,-461.5 4459,-461.5 4459,-408.5 4587,-408.5 4587,-461.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"4523\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 29</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4523\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [27, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4523\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 152&#45;&gt;153 -->\r\n",
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       "<path fill=\"none\" stroke=\"black\" d=\"M4621.6,-504.884C4604.44,-492.896 4585.12,-479.399 4568.16,-467.549\"/>\r\n",
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       "<g id=\"node155\" class=\"node\"><title>154</title>\r\n",
       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"4733,-461.5 4605,-461.5 4605,-408.5 4733,-408.5 4733,-461.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 65</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [65, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4669\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 152&#45;&gt;154 -->\r\n",
       "<g id=\"edge154\" class=\"edge\"><title>152&#45;&gt;154</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M4669,-504.884C4669,-494.326 4669,-482.597 4669,-471.854\"/>\r\n",
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       "<!-- 156 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"4806\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4806\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [7, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4806\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 155&#45;&gt;156 -->\r\n",
       "<g id=\"edge156\" class=\"edge\"><title>155&#45;&gt;156</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M4883.66,-504.884C4870.4,-493.116 4855.49,-479.894 4842.31,-468.203\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"4844.58,-465.537 4834.77,-461.52 4839.93,-470.774 4844.58,-465.537\"/>\r\n",
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       "<g id=\"node158\" class=\"node\"><title>157</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.894118\" stroke=\"black\" points=\"5116.5,-469 4879.5,-469 4879.5,-401 5116.5,-401 5116.5,-469\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"4998\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 24992.875</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4998\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 83</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4998\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [75, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4998\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 155&#45;&gt;157 -->\r\n",
       "<g id=\"edge157\" class=\"edge\"><title>155&#45;&gt;157</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M4946,-504.884C4952.59,-496.154 4959.78,-486.625 4966.66,-477.514\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"4969.63,-479.389 4972.86,-469.299 4964.04,-475.172 4969.63,-479.389\"/>\r\n",
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       "<!-- 158 -->\r\n",
       "<g id=\"node159\" class=\"node\"><title>158</title>\r\n",
       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"4989,-357.5 4861,-357.5 4861,-304.5 4989,-304.5 4989,-357.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"4925\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 63</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4925\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [63, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"4925\" y=\"-312.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 157&#45;&gt;158 -->\r\n",
       "<g id=\"edge158\" class=\"edge\"><title>157&#45;&gt;158</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M4974.3,-400.884C4966.27,-389.666 4957.3,-377.126 4949.23,-365.852\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"4951.93,-363.615 4943.26,-357.52 4946.24,-367.689 4951.93,-363.615\"/>\r\n",
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       "<!-- 159 -->\r\n",
       "<g id=\"node160\" class=\"node\"><title>159</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.333333\" stroke=\"black\" points=\"5135,-357.5 5007,-357.5 5007,-304.5 5135,-304.5 5135,-357.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5071\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 20</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5071\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [12, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5071\" y=\"-312.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 157&#45;&gt;159 -->\r\n",
       "<g id=\"edge159\" class=\"edge\"><title>157&#45;&gt;159</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M5021.7,-400.884C5029.73,-389.666 5038.7,-377.126 5046.77,-365.852\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"5049.76,-367.689 5052.74,-357.52 5044.07,-363.615 5049.76,-367.689\"/>\r\n",
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       "<!-- 162 -->\r\n",
       "<g id=\"node163\" class=\"node\"><title>162</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.870588\" stroke=\"black\" points=\"6333.5,-1301 6130.5,-1301 6130.5,-1233 6333.5,-1233 6333.5,-1301\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6232\" y=\"-1285.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 138.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6232\" y=\"-1270.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 2051</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6232\" y=\"-1255.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [1813, 238]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6232\" y=\"-1240.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 161&#45;&gt;162 -->\r\n",
       "<g id=\"edge162\" class=\"edge\"><title>161&#45;&gt;162</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6299.53,-1336.88C6290.71,-1327.89 6281.06,-1318.04 6271.88,-1308.68\"/>\r\n",
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       "<!-- 263 -->\r\n",
       "<g id=\"node264\" class=\"node\"><title>263</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.160784\" stroke=\"black\" points=\"6512.5,-1301 6351.5,-1301 6351.5,-1233 6512.5,-1233 6512.5,-1301\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6432\" y=\"-1285.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Marital Status_Div &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6432\" y=\"-1270.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 46</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6432\" y=\"-1255.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [25, 21]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6432\" y=\"-1240.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 161&#45;&gt;263 -->\r\n",
       "<g id=\"edge263\" class=\"edge\"><title>161&#45;&gt;263</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6364.47,-1336.88C6373.29,-1327.89 6382.94,-1318.04 6392.12,-1308.68\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"6394.85,-1310.89 6399.35,-1301.3 6389.85,-1305.99 6394.85,-1310.89\"/>\r\n",
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       "<!-- 163 -->\r\n",
       "<g id=\"node164\" class=\"node\"><title>163</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.862745\" stroke=\"black\" points=\"6163.5,-1197 5926.5,-1197 5926.5,-1129 6163.5,-1129 6163.5,-1197\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6045\" y=\"-1181.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 2453.2739</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6045\" y=\"-1166.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 1960</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6045\" y=\"-1151.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [1722, 238]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6045\" y=\"-1136.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 162&#45;&gt;163 -->\r\n",
       "<g id=\"edge163\" class=\"edge\"><title>162&#45;&gt;163</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6171.29,-1232.88C6153.23,-1223.04 6133.31,-1212.17 6114.73,-1202.03\"/>\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"6310,-1189.5 6182,-1189.5 6182,-1136.5 6310,-1136.5 6310,-1189.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6246\" y=\"-1174.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 91</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6246\" y=\"-1159.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [91, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6246\" y=\"-1144.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 162&#45;&gt;262 -->\r\n",
       "<g id=\"edge262\" class=\"edge\"><title>162&#45;&gt;262</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6236.55,-1232.88C6238.01,-1222.22 6239.64,-1210.35 6241.12,-1199.52\"/>\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"6075,-1085.5 5947,-1085.5 5947,-1032.5 6075,-1032.5 6075,-1085.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6011\" y=\"-1070.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 83</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6011\" y=\"-1055.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [83, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6011\" y=\"-1040.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 163&#45;&gt;164 -->\r\n",
       "<g id=\"edge164\" class=\"edge\"><title>163&#45;&gt;164</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6033.96,-1128.88C6030.37,-1118.11 6026.37,-1106.11 6022.73,-1095.18\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6208\" y=\"-1077.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 2494.042</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6208\" y=\"-1062.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 1877</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6208\" y=\"-1047.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [1639, 238]</text>\r\n",
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       "<!-- 163&#45;&gt;165 -->\r\n",
       "<g id=\"edge165\" class=\"edge\"><title>163&#45;&gt;165</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6097.92,-1128.88C6113.37,-1119.21 6130.39,-1108.56 6146.34,-1098.59\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6208\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 18.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6208\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 34</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6208\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [20, 14]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6208\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6421\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Location Code_Sub &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6421\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 1843</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6421\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [1619, 224]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6421\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
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       "<text text-anchor=\"middle\" x=\"6087\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 19</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6087\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 5]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6087\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 166&#45;&gt;167 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6224\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6224\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [6, 9]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6224\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<!-- 166&#45;&gt;168 -->\r\n",
       "<g id=\"edge168\" class=\"edge\"><title>166&#45;&gt;168</title>\r\n",
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       "<g id=\"node171\" class=\"node\"><title>170</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.905882\" stroke=\"black\" points=\"6522.5,-885 6319.5,-885 6319.5,-817 6522.5,-817 6522.5,-885\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6421\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 108.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6421\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 699</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6421\" y=\"-839.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [638, 61]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6421\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 169&#45;&gt;170 -->\r\n",
       "<g id=\"edge170\" class=\"edge\"><title>169&#45;&gt;170</title>\r\n",
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       "<polygon fill=\"black\" stroke=\"black\" points=\"6424.5,-895.299 6421,-885.299 6417.5,-895.299 6424.5,-895.299\"/>\r\n",
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       "<g id=\"node210\" class=\"node\"><title>209</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.835294\" stroke=\"black\" points=\"6905,-885 6675,-885 6675,-817 6905,-817 6905,-885\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6790\" y=\"-869.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 4.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6790\" y=\"-854.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 1144</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6790\" y=\"-839.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [981, 163]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6790\" y=\"-824.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 169&#45;&gt;209 -->\r\n",
       "<g id=\"edge209\" class=\"edge\"><title>169&#45;&gt;209</title>\r\n",
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       "<polygon fill=\"black\" stroke=\"black\" points=\"6666.05,-889.895 6674.75,-883.857 6664.18,-883.148 6666.05,-889.895\"/>\r\n",
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       "<g id=\"node172\" class=\"node\"><title>171</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.937255\" stroke=\"black\" points=\"5901,-781 5671,-781 5671,-713 5901,-713 5901,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5786\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 2773.814</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5786\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 542</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5786\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [510, 32]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5786\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 170&#45;&gt;171 -->\r\n",
       "<g id=\"edge171\" class=\"edge\"><title>170&#45;&gt;171</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6319.22,-823.573C6308.71,-821.196 6298.16,-818.953 6288,-817 6160.5,-792.492 6013.16,-773.309 5911.24,-761.457\"/>\r\n",
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       "<!-- 200 -->\r\n",
       "<g id=\"node201\" class=\"node\"><title>200</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.772549\" stroke=\"black\" points=\"6540.5,-781 6303.5,-781 6303.5,-713 6540.5,-713 6540.5,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 9095.0225</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 157</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [128, 29]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 170&#45;&gt;200 -->\r\n",
       "<g id=\"edge200\" class=\"edge\"><title>170&#45;&gt;200</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6421.32,-816.884C6421.4,-808.778 6421.49,-799.982 6421.57,-791.472\"/>\r\n",
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       "<!-- 172 -->\r\n",
       "<g id=\"node173\" class=\"node\"><title>172</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.760784\" stroke=\"black\" points=\"5617,-677 5411,-677 5411,-609 5617,-609 5617,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5514\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 15.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5514\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 62</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5514\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [50, 12]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5514\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 171&#45;&gt;172 -->\r\n",
       "<g id=\"edge172\" class=\"edge\"><title>171&#45;&gt;172</title>\r\n",
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       "<!-- 177 -->\r\n",
       "<g id=\"node178\" class=\"node\"><title>177</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.956863\" stroke=\"black\" points=\"5850,-677 5722,-677 5722,-609 5850,-609 5850,-677\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5786\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 50616.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5786\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 480</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5786\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [460, 20]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5786\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 171&#45;&gt;177 -->\r\n",
       "<g id=\"edge177\" class=\"edge\"><title>171&#45;&gt;177</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M5786,-712.884C5786,-704.778 5786,-695.982 5786,-687.472\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"5789.5,-687.299 5786,-677.299 5782.5,-687.299 5789.5,-687.299\"/>\r\n",
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       "<!-- 173 -->\r\n",
       "<g id=\"node174\" class=\"node\"><title>173</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.478431\" stroke=\"black\" points=\"5425,-573 5265,-573 5265,-505 5425,-505 5425,-573\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5345\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Marital Status_Sin &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5345\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 35</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5345\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [23, 12]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5345\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 172&#45;&gt;173 -->\r\n",
       "<g id=\"edge173\" class=\"edge\"><title>172&#45;&gt;173</title>\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"5578,-565.5 5450,-565.5 5450,-512.5 5578,-512.5 5578,-565.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5514\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 27</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5514\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [27, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5514\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 172&#45;&gt;176 -->\r\n",
       "<g id=\"edge176\" class=\"edge\"><title>172&#45;&gt;176</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M5514,-608.884C5514,-598.326 5514,-586.597 5514,-575.854\"/>\r\n",
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       "<g id=\"node175\" class=\"node\"><title>174</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.733333\" stroke=\"black\" points=\"5263,-461.5 5135,-461.5 5135,-408.5 5263,-408.5 5263,-461.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5199\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 19</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5199\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [15, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5199\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 173&#45;&gt;174 -->\r\n",
       "<g id=\"edge174\" class=\"edge\"><title>173&#45;&gt;174</title>\r\n",
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       "<!-- 175 -->\r\n",
       "<g id=\"node176\" class=\"node\"><title>175</title>\r\n",
       "<polygon fill=\"none\" stroke=\"black\" points=\"5409,-461.5 5281,-461.5 5281,-408.5 5409,-408.5 5409,-461.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5345\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 16</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5345\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [8, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5345\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 173&#45;&gt;175 -->\r\n",
       "<g id=\"edge175\" class=\"edge\"><title>173&#45;&gt;175</title>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.996078\" stroke=\"black\" points=\"5806,-573 5610,-573 5610,-505 5806,-505 5806,-573\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5708\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 65.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5708\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 206</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5708\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [205, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5708\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 177&#45;&gt;178 -->\r\n",
       "<g id=\"edge178\" class=\"edge\"><title>177&#45;&gt;178</title>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.925490\" stroke=\"black\" points=\"5952,-573 5824,-573 5824,-505 5952,-505 5952,-573\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5888\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 61442.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5888\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 274</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5888\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [255, 19]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5888\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 177&#45;&gt;183 -->\r\n",
       "<g id=\"edge183\" class=\"edge\"><title>177&#45;&gt;183</title>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.972549\" stroke=\"black\" points=\"5633,-469 5427,-469 5427,-401 5633,-401 5633,-469\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"5530\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 11.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5530\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 38</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5530\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [37, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"5530\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 178&#45;&gt;179 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"5874\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 60172.5</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"5694\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 92.0</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6020\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 98</text>\r\n",
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       "<!-- 189&#45;&gt;190 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6221\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 5827.0801</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6221\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 115</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6221\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [107, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6221\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 189&#45;&gt;191 -->\r\n",
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       "<!-- 191&#45;&gt;192 -->\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.874510\" stroke=\"black\" points=\"6319,-261 6123,-261 6123,-193 6319,-193 6319,-261\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6221\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 73.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6221\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 71</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6221\" y=\"-215.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [63, 8]</text>\r\n",
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       "<!-- 191&#45;&gt;193 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"5970\" y=\"-141.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 8158.6787</text>\r\n",
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       "<!-- 193&#45;&gt;194 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6221\" y=\"-141.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">State_California &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6221\" y=\"-126.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 40</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6116\" y=\"-37.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 25</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6262\" y=\"-37.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6262\" y=\"-22.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [13, 2]</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6422\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 8833.5098</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 92</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6623\" y=\"-654.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 65</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6422\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 61.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 71</text>\r\n",
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       "<!-- 201&#45;&gt;202 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6614\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<!-- 201&#45;&gt;207 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6422\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Education_College &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 42</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [38, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 202&#45;&gt;203 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6586\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 29</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6586\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 202&#45;&gt;206 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6422\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 27</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [27, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6422\" y=\"-312.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 203&#45;&gt;204 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6568\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6568\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [11, 4]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6568\" y=\"-312.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 203&#45;&gt;205 -->\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.513725\" stroke=\"black\" points=\"6854,-781 6726,-781 6726,-713 6854,-713 6854,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6790\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 14152.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6790\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 58</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6790\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [39, 19]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6790\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 209&#45;&gt;210 -->\r\n",
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       "<path fill=\"none\" stroke=\"black\" d=\"M6790,-816.884C6790,-808.778 6790,-799.982 6790,-791.472\"/>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.847059\" stroke=\"black\" points=\"7672,-781 7544,-781 7544,-713 7672,-713 7672,-781\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7608\" y=\"-765.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 56940.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7608\" y=\"-750.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 1086</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7608\" y=\"-735.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [942, 144]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7608\" y=\"-720.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 209&#45;&gt;215 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6788\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Education_College &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6788\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 37</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6788\" y=\"-631.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [18, 19]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6788\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<!-- 210&#45;&gt;211 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6952\" y=\"-654.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 21</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6952\" y=\"-639.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [21, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6952\" y=\"-624.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<g id=\"edge214\" class=\"edge\"><title>210&#45;&gt;214</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"6769\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 17</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6906\" y=\"-550.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 20</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6906\" y=\"-535.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [7, 13]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6906\" y=\"-520.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"7608\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Education_Doctor &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7608\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 880</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"8089\" y=\"-661.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 100.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8089\" y=\"-646.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 206</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"8089\" y=\"-616.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"7512\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">EmploymentStatus_Disabled &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7512\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 850</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7512\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [768, 82]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7512\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"7704\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 23326.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7704\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 30</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"7250\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 123.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7250\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 795</text>\r\n",
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       "<!-- 217&#45;&gt;218 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"7533\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Gender_M &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7533\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 55</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7533\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [41, 14]</text>\r\n",
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       "<!-- 217&#45;&gt;237 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6945\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 16310.5625</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6945\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 714</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6945\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [662, 52]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6945\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 218&#45;&gt;219 -->\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.752941\" stroke=\"black\" points=\"7353,-365 7147,-365 7147,-297 7353,-297 7353,-365\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7250\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 27.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7250\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 81</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7250\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [65, 16]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7250\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6700\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 7287.5503</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6700\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 657</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6700\" y=\"-215.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [618, 39]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6700\" y=\"-200.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 219&#45;&gt;220 -->\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.705882\" stroke=\"black\" points=\"7048,-261 6842,-261 6842,-193 7048,-193 7048,-261\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6945\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 10.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6945\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 57</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6945\" y=\"-215.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [44, 13]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6945\" y=\"-200.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 219&#45;&gt;227 -->\r\n",
       "<g id=\"edge227\" class=\"edge\"><title>219&#45;&gt;227</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6945,-296.884C6945,-288.778 6945,-279.982 6945,-271.472\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6497\" y=\"-141.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Number of Policies &lt;= 6.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6497\" y=\"-126.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 446</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6497\" y=\"-111.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [410, 36]</text>\r\n",
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       "<!-- 220&#45;&gt;221 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6700\" y=\"-141.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 117.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6700\" y=\"-126.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 211</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6700\" y=\"-111.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [208, 3]</text>\r\n",
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       "<!-- 220&#45;&gt;224 -->\r\n",
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       "<!-- 221&#45;&gt;222 -->\r\n",
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       "<path fill=\"none\" stroke=\"black\" d=\"M6465.87,-88.9485C6457.26,-79.8005 6447.9,-69.8697 6439.28,-60.7126\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6700\" y=\"-37.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 196</text>\r\n",
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       "<g id=\"edge229\" class=\"edge\"><title>227&#45;&gt;229</title>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.858824\" stroke=\"black\" points=\"7314,-261 7068,-261 7068,-193 7314,-193 7314,-261\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7191\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Education_High School or Below &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7191\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 65</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7191\" y=\"-215.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [57, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7191\" y=\"-200.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 230&#45;&gt;231 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"7396\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 16</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7396\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [8, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7396\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 230&#45;&gt;236 -->\r\n",
       "<g id=\"edge236\" class=\"edge\"><title>230&#45;&gt;236</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"7194\" y=\"-141.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Education_College &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7194\" y=\"-126.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 42</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7194\" y=\"-111.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [34, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7194\" y=\"-96.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 231&#45;&gt;232 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"7358\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 23</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7358\" y=\"-119.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [23, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7358\" y=\"-104.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 231&#45;&gt;235 -->\r\n",
       "<g id=\"edge235\" class=\"edge\"><title>231&#45;&gt;235</title>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.333333\" stroke=\"black\" points=\"7185,-53 7057,-53 7057,-0 7185,-0 7185,-53\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7121\" y=\"-37.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 20</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7121\" y=\"-22.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [12, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7121\" y=\"-7.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 232&#45;&gt;233 -->\r\n",
       "<g id=\"edge233\" class=\"edge\"><title>232&#45;&gt;233</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M7168.47,-88.9485C7161.54,-79.9834 7154.04,-70.2666 7147.08,-61.2629\"/>\r\n",
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       "<!-- 234 -->\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"7331,-53 7203,-53 7203,-0 7331,-0 7331,-53\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7267\" y=\"-37.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 22</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7267\" y=\"-22.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [22, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7267\" y=\"-7.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 232&#45;&gt;234 -->\r\n",
       "<g id=\"edge234\" class=\"edge\"><title>232&#45;&gt;234</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M7219.53,-88.9485C7226.46,-79.9834 7233.96,-70.2666 7240.92,-61.2629\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"7243.78,-63.2902 7247.12,-53.2367 7238.24,-59.0108 7243.78,-63.2902\"/>\r\n",
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       "<!-- 238 -->\r\n",
       "<g id=\"node239\" class=\"node\"><title>238</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.392157\" stroke=\"black\" points=\"7636,-365 7430,-365 7430,-297 7636,-297 7636,-365\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7533\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Last Claim &lt;= 11.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7533\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 37</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7533\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [23, 14]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7533\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 237&#45;&gt;238 -->\r\n",
       "<g id=\"edge238\" class=\"edge\"><title>237&#45;&gt;238</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M7533,-400.884C7533,-392.778 7533,-383.982 7533,-375.472\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"7536.5,-375.299 7533,-365.299 7529.5,-375.299 7536.5,-375.299\"/>\r\n",
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       "<!-- 241 -->\r\n",
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       "<polygon fill=\"#e58139\" stroke=\"black\" points=\"7782,-357.5 7654,-357.5 7654,-304.5 7782,-304.5 7782,-357.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7718\" y=\"-342.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 18</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7718\" y=\"-327.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [18, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7718\" y=\"-312.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 237&#45;&gt;241 -->\r\n",
       "<g id=\"edge241\" class=\"edge\"><title>237&#45;&gt;241</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M7593.06,-400.884C7615.5,-388.511 7640.86,-374.53 7662.84,-362.413\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"7533\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 19</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7533\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [8, 11]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7533\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 238&#45;&gt;239 -->\r\n",
       "<g id=\"edge239\" class=\"edge\"><title>238&#45;&gt;239</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M7533,-296.884C7533,-286.326 7533,-274.597 7533,-263.854\"/>\r\n",
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       "<!-- 240 -->\r\n",
       "<g id=\"node241\" class=\"node\"><title>240</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.800000\" stroke=\"black\" points=\"7734,-253.5 7606,-253.5 7606,-200.5 7734,-200.5 7734,-253.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7670\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 18</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7670\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [15, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7670\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 238&#45;&gt;240 -->\r\n",
       "<g id=\"edge240\" class=\"edge\"><title>238&#45;&gt;240</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M7577.48,-296.884C7593.58,-284.896 7611.71,-271.399 7627.62,-259.549\"/>\r\n",
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       "<!-- 243 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"7683\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7683\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [13, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7683\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 242&#45;&gt;243 -->\r\n",
       "<g id=\"edge243\" class=\"edge\"><title>242&#45;&gt;243</title>\r\n",
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       "<!-- 244 -->\r\n",
       "<g id=\"node245\" class=\"node\"><title>244</title>\r\n",
       "<polygon fill=\"#399de5\" fill-opacity=\"0.635294\" stroke=\"black\" points=\"7875,-461.5 7765,-461.5 7765,-408.5 7875,-408.5 7875,-461.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7820\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7820\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [4, 11]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7820\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 242&#45;&gt;244 -->\r\n",
       "<g id=\"edge244\" class=\"edge\"><title>242&#45;&gt;244</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M7741.66,-504.884C7755.04,-493.116 7770.08,-479.894 7783.38,-468.203\"/>\r\n",
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       "<!-- 246 -->\r\n",
       "<g id=\"node247\" class=\"node\"><title>246</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.584314\" stroke=\"black\" points=\"8187,-573 7991,-573 7991,-505 8187,-505 8187,-573\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"8089\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Monthly Premium Auto &lt;= 93.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8089\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 146</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8089\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [103, 43]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8089\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 245&#45;&gt;246 -->\r\n",
       "<g id=\"edge246\" class=\"edge\"><title>245&#45;&gt;246</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M8089,-608.884C8089,-600.778 8089,-591.982 8089,-583.472\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"8092.5,-583.299 8089,-573.299 8085.5,-583.299 8092.5,-583.299\"/>\r\n",
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       "<g id=\"node260\" class=\"node\"><title>259</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.890196\" stroke=\"black\" points=\"8407,-573 8279,-573 8279,-505 8407,-505 8407,-573\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"8343\" y=\"-557.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 59381.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8343\" y=\"-542.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 60</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8343\" y=\"-527.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [54, 6]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8343\" y=\"-512.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 245&#45;&gt;259 -->\r\n",
       "<g id=\"edge259\" class=\"edge\"><title>245&#45;&gt;259</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M8171.47,-608.884C8202.97,-596.231 8238.67,-581.898 8269.3,-569.595\"/>\r\n",
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       "<g id=\"node248\" class=\"node\"><title>247</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.678431\" stroke=\"black\" points=\"8132.5,-469 7895.5,-469 7895.5,-401 8132.5,-401 8132.5,-469\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"8014\" y=\"-453.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Months Since Policy Inception &lt;= 64.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8014\" y=\"-438.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 127</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8014\" y=\"-423.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [96, 31]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8014\" y=\"-408.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 246&#45;&gt;247 -->\r\n",
       "<g id=\"edge247\" class=\"edge\"><title>246&#45;&gt;247</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"8206\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 19</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8206\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [7, 12]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8206\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<!-- 246&#45;&gt;258 -->\r\n",
       "<g id=\"edge258\" class=\"edge\"><title>246&#45;&gt;258</title>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.823529\" stroke=\"black\" points=\"8078,-365 7950,-365 7950,-297 8078,-297 8078,-365\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"8014\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 73510.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8014\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 73</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8014\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [62, 11]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8014\" y=\"-304.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 247&#45;&gt;248 -->\r\n",
       "<g id=\"edge248\" class=\"edge\"><title>247&#45;&gt;248</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"8218\" y=\"-349.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 82445.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8218\" y=\"-334.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 54</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8218\" y=\"-319.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [34, 20]</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"7816\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 70411.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7816\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 38</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"8017\" y=\"-245.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 5765.2812</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8017\" y=\"-230.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 35</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"7832\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"8001\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 20</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"8001\" y=\"-104.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 252&#45;&gt;253 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"8147\" y=\"-134.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8147\" y=\"-119.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 1]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8147\" y=\"-104.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 252&#45;&gt;254 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"8218\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 26</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"8218\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"8355\" y=\"-238.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 28</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8355\" y=\"-223.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [13, 15]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8355\" y=\"-208.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<!-- 255&#45;&gt;257 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"8343\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 17</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8343\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [11, 6]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8343\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 259&#45;&gt;260 -->\r\n",
       "<g id=\"edge260\" class=\"edge\"><title>259&#45;&gt;260</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"8489\" y=\"-446.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 43</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8489\" y=\"-431.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [43, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"8489\" y=\"-416.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 259&#45;&gt;261 -->\r\n",
       "<g id=\"edge261\" class=\"edge\"><title>259&#45;&gt;261</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M8390.4,-504.884C8407.56,-492.896 8426.88,-479.399 8443.84,-467.549\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6405\" y=\"-1181.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 51573.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6405\" y=\"-1166.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 30</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6405\" y=\"-1151.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [22, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6405\" y=\"-1136.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 263&#45;&gt;264 -->\r\n",
       "<g id=\"edge264\" class=\"edge\"><title>263&#45;&gt;264</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6423.23,-1232.88C6421.06,-1224.69 6418.71,-1215.79 6416.43,-1207.19\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6542\" y=\"-1174.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 16</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6542\" y=\"-1159.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [3, 13]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6542\" y=\"-1144.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<!-- 263&#45;&gt;267 -->\r\n",
       "<g id=\"edge267\" class=\"edge\"><title>263&#45;&gt;267</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6467.71,-1232.88C6480.29,-1221.23 6494.4,-1208.14 6506.92,-1196.53\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6405\" y=\"-1070.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6405\" y=\"-1055.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [15, 0]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6405\" y=\"-1040.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 264&#45;&gt;265 -->\r\n",
       "<g id=\"edge265\" class=\"edge\"><title>264&#45;&gt;265</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"6542\" y=\"-1070.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 15</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6542\" y=\"-1055.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [7, 8]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6542\" y=\"-1040.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<!-- 264&#45;&gt;266 -->\r\n",
       "<g id=\"edge266\" class=\"edge\"><title>264&#45;&gt;266</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6449.48,-1128.88C6465.58,-1116.9 6483.71,-1103.4 6499.62,-1091.55\"/>\r\n",
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       "<text text-anchor=\"middle\" x=\"6696\" y=\"-1389.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 14588.7832</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6696\" y=\"-1374.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 146</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6696\" y=\"-1359.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [65, 81]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6696\" y=\"-1344.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<!-- 268&#45;&gt;269 -->\r\n",
       "<g id=\"edge269\" class=\"edge\"><title>268&#45;&gt;269</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"6944\" y=\"-1389.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Marital Status_Div &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6944\" y=\"-1374.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 39</text>\r\n",
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       "<text text-anchor=\"middle\" x=\"6670\" y=\"-1285.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 13608.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6670\" y=\"-1270.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 128</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6670\" y=\"-1255.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [62, 66]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6670\" y=\"-1240.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
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       "<!-- 269&#45;&gt;270 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"6807\" y=\"-1278.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 18</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6807\" y=\"-1263.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [3, 15]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6807\" y=\"-1248.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 269&#45;&gt;281 -->\r\n",
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       "<!-- 271 -->\r\n",
       "<g id=\"node272\" class=\"node\"><title>271</title>\r\n",
       "<polygon fill=\"#399de5\" fill-opacity=\"0.733333\" stroke=\"black\" points=\"6725,-1189.5 6615,-1189.5 6615,-1136.5 6725,-1136.5 6725,-1189.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6670\" y=\"-1174.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 19</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6670\" y=\"-1159.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [4, 15]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6670\" y=\"-1144.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 270&#45;&gt;271 -->\r\n",
       "<g id=\"edge271\" class=\"edge\"><title>270&#45;&gt;271</title>\r\n",
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       "<polygon fill=\"black\" stroke=\"black\" points=\"6673.5,-1199.52 6670,-1189.52 6666.5,-1199.52 6673.5,-1199.52\"/>\r\n",
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       "<!-- 272 -->\r\n",
       "<g id=\"node273\" class=\"node\"><title>272</title>\r\n",
       "<polygon fill=\"#e58139\" fill-opacity=\"0.121569\" stroke=\"black\" points=\"6980.5,-1197 6743.5,-1197 6743.5,-1129 6980.5,-1129 6980.5,-1197\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6862\" y=\"-1181.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Customer Lifetime Value &lt;= 3650.6597</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6862\" y=\"-1166.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 109</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6862\" y=\"-1151.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [58, 51]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6862\" y=\"-1136.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 270&#45;&gt;272 -->\r\n",
       "<g id=\"edge272\" class=\"edge\"><title>270&#45;&gt;272</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6732.34,-1232.88C6750.96,-1222.99 6771.52,-1212.07 6790.67,-1201.9\"/>\r\n",
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       "<!-- 273 -->\r\n",
       "<g id=\"node274\" class=\"node\"><title>273</title>\r\n",
       "<polygon fill=\"#399de5\" fill-opacity=\"0.454902\" stroke=\"black\" points=\"6898.5,-1093 6727.5,-1093 6727.5,-1025 6898.5,-1025 6898.5,-1093\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6813\" y=\"-1077.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Education_Bachelor &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6813\" y=\"-1062.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 34</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6813\" y=\"-1047.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [12, 22]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6813\" y=\"-1032.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 272&#45;&gt;273 -->\r\n",
       "<g id=\"edge273\" class=\"edge\"><title>272&#45;&gt;273</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6846.09,-1128.88C6842.03,-1120.42 6837.6,-1111.21 6833.35,-1102.35\"/>\r\n",
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       "<!-- 276 -->\r\n",
       "<g id=\"node277\" class=\"node\"><title>276</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"7027\" y=\"-1077.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Number of Open Complaints &lt;= 0.5</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7027\" y=\"-1062.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 75</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7027\" y=\"-1047.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [46, 29]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7027\" y=\"-1032.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 272&#45;&gt;276 -->\r\n",
       "<g id=\"edge276\" class=\"edge\"><title>272&#45;&gt;276</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6915.57,-1128.88C6931.21,-1119.21 6948.44,-1108.56 6964.58,-1098.59\"/>\r\n",
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       "<polygon fill=\"#399de5\" fill-opacity=\"0.109804\" stroke=\"black\" points=\"6766,-981.5 6656,-981.5 6656,-928.5 6766,-928.5 6766,-981.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6711\" y=\"-966.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 17</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6711\" y=\"-951.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [8, 9]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6711\" y=\"-936.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 273&#45;&gt;274 -->\r\n",
       "<g id=\"edge274\" class=\"edge\"><title>273&#45;&gt;274</title>\r\n",
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       "<polygon fill=\"black\" stroke=\"black\" points=\"6746.07,-986.116 6736.52,-981.52 6741.12,-991.066 6746.07,-986.116\"/>\r\n",
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       "<g id=\"node276\" class=\"node\"><title>275</title>\r\n",
       "<polygon fill=\"#399de5\" fill-opacity=\"0.694118\" stroke=\"black\" points=\"6894,-981.5 6784,-981.5 6784,-928.5 6894,-928.5 6894,-981.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6839\" y=\"-966.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 17</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6839\" y=\"-951.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [4, 13]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6839\" y=\"-936.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = response</text>\r\n",
       "</g>\r\n",
       "<!-- 273&#45;&gt;275 -->\r\n",
       "<g id=\"edge275\" class=\"edge\"><title>273&#45;&gt;275</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6821.44,-1024.88C6824.16,-1014.22 6827.18,-1002.35 6829.95,-991.519\"/>\r\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"6833.42,-992.075 6832.49,-981.52 6826.63,-990.346 6833.42,-992.075\"/>\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.619608\" stroke=\"black\" points=\"7066,-989 6938,-989 6938,-921 7066,-921 7066,-989\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"7002\" y=\"-973.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">Income &lt;= 26718.0</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7002\" y=\"-958.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 47</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7002\" y=\"-943.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [34, 13]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7002\" y=\"-928.8\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 276&#45;&gt;277 -->\r\n",
       "<g id=\"edge277\" class=\"edge\"><title>276&#45;&gt;277</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"7139\" y=\"-966.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 28</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7139\" y=\"-951.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [12, 16]</text>\r\n",
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       "</g>\r\n",
       "<!-- 276&#45;&gt;280 -->\r\n",
       "<g id=\"edge280\" class=\"edge\"><title>276&#45;&gt;280</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"6990\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [22, 3]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6990\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 277&#45;&gt;278 -->\r\n",
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       "<text text-anchor=\"middle\" x=\"7136\" y=\"-862.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 22</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7136\" y=\"-847.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [12, 10]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7136\" y=\"-832.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<!-- 277&#45;&gt;279 -->\r\n",
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       "<polygon fill=\"#e58139\" fill-opacity=\"0.858824\" stroke=\"black\" points=\"7008,-1293.5 6880,-1293.5 6880,-1240.5 7008,-1240.5 7008,-1293.5\"/>\r\n",
       "<text text-anchor=\"middle\" x=\"6944\" y=\"-1278.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 16</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6944\" y=\"-1263.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [14, 2]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"6944\" y=\"-1248.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
       "</g>\r\n",
       "<!-- 282&#45;&gt;283 -->\r\n",
       "<g id=\"edge283\" class=\"edge\"><title>282&#45;&gt;283</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6944,-1336.88C6944,-1326.33 6944,-1314.6 6944,-1303.85\"/>\r\n",
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       "<g id=\"node285\" class=\"node\"><title>284</title>\r\n",
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       "<text text-anchor=\"middle\" x=\"7090\" y=\"-1278.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">samples = 23</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7090\" y=\"-1263.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">value = [13, 10]</text>\r\n",
       "<text text-anchor=\"middle\" x=\"7090\" y=\"-1248.3\" font-family=\"Times New Roman,serif\" font-size=\"14.00\">class = no response</text>\r\n",
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       "<g id=\"edge284\" class=\"edge\"><title>282&#45;&gt;284</title>\r\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M6991.4,-1336.88C7008.56,-1324.9 7027.88,-1311.4 7044.84,-1299.55\"/>\r\n",
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       "</g>\r\n",
       "</g>\r\n",
       "</svg>\r\n"
      ],
      "text/plain": [
       "<graphviz.files.Source at 0x1cc130c5e80>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import graphviz\n",
    "\n",
    "with open(\"tree2.dot\") as f:\n",
    "    dot_graph = f.read()\n",
    "graphviz.Source(dot_graph)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cc1317fbe0>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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0DGjsnPsduNzM/gomEDN7Cngqn3Vj8PfA5CwfC4wNZn+B2r0batUCn0cnsKat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\nE3LDDf6ekGXL/s720tLSrM0rbezC9y6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JISEhGDNmDOrWrYvk5GScPXsWycnJOnfee5b9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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc1313db00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tr_auc = roc_auc_score(y_control, tree2.predict_proba(X_control)[:, 1])\n",
    "fpr_tr2, tpr_tr2, thresholds_tr2 = roc_curve(y_control, tree2.predict_proba(X_control)[:, 1])\n",
    "plt.plot(fpr_rf2, tpr_rf2, label='ROC-кривая случайного леса (AUC = %0.2f)' % rf_auc)\n",
    "plt.plot(fpr_tr2, tpr_tr2, label='ROC-кривая дерева (AUC = %0.2f)' % tr_auc)\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR (полнота)\")\n",
    "plt.legend(loc=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Улучшение качества модели случайного леса"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Методы перекрестной проверки, реализованные в scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import cross_val_score, KFold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "kfold = KFold(n_splits=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Значения правильности перекрестной проверки:\n",
      "[ 0.89759036  0.94578313  0.94819277  0.95657419  0.93124246  0.93003619\n",
      "  0.92882992  0.93486128  0.93124246  0.92159228]\n"
     ]
    }
   ],
   "source": [
    "print(\"Значения правильности перекрестной проверки:\\n{}\".\n",
    "      format(cross_val_score(forest2, X, y, cv=kfold)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Среднее значение правильности перекрестной проверки: 0.93\n"
     ]
    }
   ],
   "source": [
    "kfold = KFold(n_splits=10)\n",
    "scores_acc_rf = cross_val_score(forest2, X, y, cv=kfold)\n",
    "print(\"Среднее значение правильности перекрестной проверки: {:.2f}\".\n",
    "      format(scores_acc_rf.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Среднее значение AUC перекрестной проверки: 0.96\n"
     ]
    }
   ],
   "source": [
    "kfold = KFold(n_splits=10)\n",
    "scores_auc_rf = cross_val_score(forest2, X, y, scoring='roc_auc', cv=kfold)\n",
    "print(\"Среднее значение AUC перекрестной проверки: {:.2f}\".\n",
    "      format(scores_auc_rf.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Среднее значение AUC перекрестной проверки: 0.96 (+/- 0.03)\n"
     ]
    }
   ],
   "source": [
    "kfold = KFold(n_splits=10)\n",
    "scores_auc_rf = cross_val_score(forest2, X, y, scoring='roc_auc', cv=kfold)\n",
    "print(\"Среднее значение AUC перекрестной проверки: %0.2f (+/- %0.2f)\" % \n",
    "      (scores_auc_rf.mean(), scores_auc_rf.std() * 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Среднее значение AUC перекрестной проверки: 0.96\n"
     ]
    }
   ],
   "source": [
    "kfold = KFold(n_splits=10, shuffle=True, random_state=42)\n",
    "scores_auc_rf = cross_val_score(forest2, X, y, scoring='roc_auc', cv=kfold)\n",
    "print(\"Среднее значение AUC перекрестной проверки: {:.2f}\".\n",
    "      format(scores_auc_rf.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Среднее значение AUC перекрестной проверки с перестановками: 0.93\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import ShuffleSplit\n",
    "shuffle_split = ShuffleSplit(test_size=.3, train_size=.7, random_state=42, n_splits=10)\n",
    "scores = cross_val_score(forest2, X, y, scoring='roc_auc', cv=shuffle_split)\n",
    "print(\"Среднее значение AUC перекрестной проверки с перестановками: {:.2f}\".\n",
    "      format(scores.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Среднее значение AUC стратифицированной перекрестной проверки: 0.96\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import StratifiedKFold\n",
    "strat_split = StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n",
    "scores = cross_val_score(forest2, X, y, scoring='roc_auc', cv=strat_split)\n",
    "print(\"Среднее значение AUC стратифицированной перекрестной проверки: {:.2f}\".\n",
    "      format(scores.mean()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Поиск оптимальных параметров случайного леса"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Получение базовой информации для решетчатого поиска"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Наилучшее значение правильности перекрестной проверки равно 93.83% и достигается при 25 деревьях\n"
     ]
    }
   ],
   "source": [
    "# Отключаем предупреждения Anaconda\n",
    "import warnings\n",
    "warnings.simplefilter('ignore')\n",
    "\n",
    "# Создаем экземляр класса StratifiedKFold \n",
    "strat = StratifiedKFold(n_splits=10, shuffle=True, random_state=42)\n",
    "\n",
    "# Создаем списки для сохранения правильности на обучающей и контрольной выборках\n",
    "train_acc = []\n",
    "test_acc = []\n",
    "temp_train_acc = []\n",
    "temp_test_acc = []\n",
    "trees_grid = [5, 10, 25, 50, 100, 150, 200, 250, 300]\n",
    "\n",
    "# Строим модели с разным количеством деревьев\n",
    "for ntrees in trees_grid:\n",
    "    rf = RandomForestClassifier(n_estimators=ntrees, random_state=42, n_jobs=-1)\n",
    "    temp_train_acc = []\n",
    "    temp_test_acc = []\n",
    "    for train_index, test_index in strat.split(X, y):\n",
    "        X_train, X_test = X.iloc[train_index], X.iloc[test_index]\n",
    "        y_train, y_test = y[train_index], y[test_index]\n",
    "        rf.fit(X_train, y_train)\n",
    "        temp_train_acc.append(rf.score(X_train, y_train))\n",
    "        temp_test_acc.append(rf.score(X_test, y_test))\n",
    "    train_acc.append(temp_train_acc)\n",
    "    test_acc.append(temp_test_acc)\n",
    "\n",
    "# Преобразуем списки в массивы NumPy\n",
    "train_acc, test_acc = np.asarray(train_acc), np.asarray(test_acc)\n",
    "print(\"Наилучшее значение правильности перекрестной проверки равно {:.2f}% и достигается при {} деревьях\".format(max(test_acc.mean(axis=1))*100, \n",
    "                                                        trees_grid[np.argmax(test_acc.mean(axis=1))]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1cc12fea048>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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GfPHFF9Dr9cjPz8e8efMQFRWlqp6DBw/iwIEDWLhwIdLS0nDkyBGsXbsWGzZsQHJysuI2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\nhCil/wNaXnIQazgUpgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc1313dc50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "ax.plot(trees_grid, train_acc.mean(axis=1), alpha=0.5, color='blue', \n",
    "        label='обучение')\n",
    "ax.plot(trees_grid, test_acc.mean(axis=1), alpha=0.5, color='red', \n",
    "        label='перекрестная проверка')\n",
    "ax.fill_between(trees_grid, test_acc.mean(axis=1) - test_acc.std(axis=1), test_acc.mean(axis=1) + test_acc.std(axis=1), color='#888888', alpha=0.4)\n",
    "ax.fill_between(trees_grid, test_acc.mean(axis=1) - 2*test_acc.std(axis=1), test_acc.mean(axis=1) + 2*test_acc.std(axis=1), color='#888888', alpha=0.2)\n",
    "ax.legend(loc='best')\n",
    "ax.set_ylim([0.88,1.00])\n",
    "ax.set_ylabel(\"Правильность\")\n",
    "ax.set_xlabel(\"Количество деревьев\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Наилучшее значение AUC перекрестной проверки равно 0.957 и достигается при 300 деревьях\n"
     ]
    }
   ],
   "source": [
    "# Создаем списки для сохранения AUC на обучающей и контрольной выборках\n",
    "train_auc = []\n",
    "test_auc = []\n",
    "temp_train_auc = []\n",
    "temp_test_auc = []\n",
    "trees_grid = [5, 10, 25, 50, 100, 150, 200, 250, 300]\n",
    "\n",
    "# Строим модели с разным количеством деревьев\n",
    "for ntrees in trees_grid:\n",
    "    rf = RandomForestClassifier(n_estimators=ntrees, random_state=42, n_jobs=-1)\n",
    "    temp_train_auc = []\n",
    "    temp_test_auc = []\n",
    "    for train_index, test_index in strat.split(X, y):\n",
    "        X_train, X_test = X.iloc[train_index], X.iloc[test_index]\n",
    "        y_train, y_test = y[train_index], y[test_index]\n",
    "        rf.fit(X_train, y_train)\n",
    "        temp_train_auc.append(roc_auc_score(y_train, rf.predict_proba(X_train)[:, 1]))\n",
    "        temp_test_auc.append(roc_auc_score(y_test, rf.predict_proba(X_test)[:, 1]))\n",
    "    train_auc.append(temp_train_auc)\n",
    "    test_auc.append(temp_test_auc)\n",
    "\n",
    "# Преобразуем списки в массивы NumPy\n",
    "train_auc, test_auc = np.asarray(train_auc), np.asarray(test_auc)\n",
    "print(\"Наилучшее значение AUC перекрестной проверки равно {:.3f} и достигается при {} деревьях\".format(max(test_auc.mean(axis=1)), \n",
    "                                                        trees_grid[np.argmax(test_auc.mean(axis=1))]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1cc12f741d0>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lMK3RaKDX66HVar292Eo5LiIiIkoNxYVoWSw9gQaDAY888giee+45LF++HGq1Gnl5ebBY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\nJMAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc12fd2fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "ax.plot(trees_grid, train_auc.mean(axis=1), alpha=0.5, color='blue', \n",
    "        label='обучение')\n",
    "ax.plot(trees_grid, test_auc.mean(axis=1), alpha=0.5, color='red', \n",
    "        label='перекрестная проверка')\n",
    "ax.fill_between(trees_grid, test_auc.mean(axis=1) - test_auc.std(axis=1), test_auc.mean(axis=1) + test_auc.std(axis=1), color='#888888', alpha=0.4)\n",
    "ax.fill_between(trees_grid, test_auc.mean(axis=1) - 2*test_auc.std(axis=1), test_auc.mean(axis=1) + 2*test_auc.std(axis=1), color='#888888', alpha=0.2)\n",
    "ax.legend(loc='best')\n",
    "ax.set_ylim([0.88,1.02])\n",
    "ax.set_ylabel(\"AUC\")\n",
    "ax.set_xlabel(\"Количество деревьев\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Наилучшее значение AUC перекрестной проверки равно 0.959 и достигается при 12 предикторах\n"
     ]
    }
   ],
   "source": [
    "# Создаем списки для сохранения AUC на обучающей и контрольной выборках\n",
    "train_auc = []\n",
    "test_auc = []\n",
    "temp_train_auc = []\n",
    "temp_test_auc = []\n",
    "max_features_grid = [3, 6, 9, 12, 15, 18, 21, 24, 27, 30]\n",
    "\n",
    "# Строим модели с разным количеством признаков\n",
    "for max_features in max_features_grid:\n",
    "    rf = RandomForestClassifier(n_estimators=300, random_state=42, n_jobs=-1, max_features=max_features)\n",
    "    temp_train_auc = []\n",
    "    temp_test_auc = []\n",
    "    for train_index, test_index in strat.split(X, y):\n",
    "        X_train, X_test = X.iloc[train_index], X.iloc[test_index]\n",
    "        y_train, y_test = y[train_index], y[test_index]\n",
    "        rf.fit(X_train, y_train)\n",
    "        temp_train_auc.append(roc_auc_score(y_train, rf.predict_proba(X_train)[:, 1]))\n",
    "        temp_test_auc.append(roc_auc_score(y_test, rf.predict_proba(X_test)[:, 1]))\n",
    "    train_auc.append(temp_train_auc)\n",
    "    test_auc.append(temp_test_auc)\n",
    "\n",
    "# Преобразуем списки в массивы NumPy\n",
    "train_auc, test_auc = np.asarray(train_auc), np.asarray(test_auc)\n",
    "print(\"Наилучшее значение AUC перекрестной проверки равно {:.3f} и достигается при {} предикторах\".format(max(test_auc.mean(axis=1)), \n",
    "                                                        max_features_grid[np.argmax(test_auc.mean(axis=1))]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1cc12ff22b0>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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vUnBXawUHIP5eS+/lv+XS33SpYBr+WmsaaV0HS+11LBYLevfujfz8/EbPV05zgRkARo0a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\nhBBCiAL/B8U/1W9GV6nmAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc0efb1080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "ax.plot(max_features_grid, train_auc.mean(axis=1), alpha=0.5, color='blue', label='обучение')\n",
    "ax.plot(max_features_grid, test_auc.mean(axis=1), alpha=0.5, color='red', label='перекрестная проверка')\n",
    "ax.fill_between(max_features_grid, test_auc.mean(axis=1) - test_auc.std(axis=1), test_auc.mean(axis=1) + test_auc.std(axis=1), color='#888888', alpha=0.4)\n",
    "ax.fill_between(max_features_grid, test_auc.mean(axis=1) - 2*test_auc.std(axis=1), test_auc.mean(axis=1) + 2*test_auc.std(axis=1), color='#888888', alpha=0.2)\n",
    "ax.legend(loc='best')\n",
    "ax.set_ylim([0.88,1.02])\n",
    "ax.set_ylabel(\"AUC\")\n",
    "ax.set_xlabel(\"Количество случайно отбираемых предикторов для разбиения\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Наилучшее значение AUC перекрестной проверки равно 0.961 и достигается при максимальной глубине 16\n"
     ]
    }
   ],
   "source": [
    "# Создаем списки для сохранения AUC на обучающей и контрольной выборках\n",
    "train_auc = []\n",
    "test_auc = []\n",
    "temp_train_auc = []\n",
    "temp_test_auc = []\n",
    "max_depth_grid = [4, 6, 8, 10, 12, 14, 16, 18, 20, 22]\n",
    "\n",
    "# Строим модели с разным значением глубины\n",
    "for max_depth in max_depth_grid:\n",
    "    rf = RandomForestClassifier(n_estimators=300, random_state=42, n_jobs=-1, max_depth=max_depth)\n",
    "    temp_train_auc = []\n",
    "    temp_test_auc = []\n",
    "    for train_index, test_index in strat.split(X, y):\n",
    "        X_train, X_test = X.iloc[train_index], X.iloc[test_index]\n",
    "        y_train, y_test = y[train_index], y[test_index]\n",
    "        rf.fit(X_train, y_train)\n",
    "        temp_train_auc.append(roc_auc_score(y_train, rf.predict_proba(X_train)[:, 1]))\n",
    "        temp_test_auc.append(roc_auc_score(y_test, rf.predict_proba(X_test)[:, 1]))\n",
    "    train_auc.append(temp_train_auc)\n",
    "    test_auc.append(temp_test_auc)\n",
    "\n",
    "# Преобразуем списки в массивы NumPy\n",
    "train_auc, test_auc = np.asarray(train_auc), np.asarray(test_auc)\n",
    "print(\"Наилучшее значение AUC перекрестной проверки равно {:.3f} и достигается при максимальной глубине {}\".format(max(test_auc.mean(axis=1)), \n",
    "                                                        max_depth_grid[np.argmax(test_auc.mean(axis=1))]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1cc12f4b940>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KHVP+ucm+b52L7LBvLZvuHEuShFRq8vqJ7ICfH+zzw3+xdYhoZuouMFtm0nbK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\nby25vqqq+PWvf43+/n5Eo1GsWLEC+/b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wL1KJRAKRSCQTWM+fd2N42IlduyYqmTG6LNXq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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc134bfd68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "ax.plot(max_depth_grid, train_auc.mean(axis=1), alpha=0.5, color='blue', label='обучение')\n",
    "ax.plot(max_depth_grid, test_auc.mean(axis=1), alpha=0.5, color='red', label='перекрестная проверка')\n",
    "ax.fill_between(max_depth_grid, test_auc.mean(axis=1) - test_auc.std(axis=1), test_auc.mean(axis=1) + test_auc.std(axis=1), color='#888888', alpha=0.4)\n",
    "ax.fill_between(max_depth_grid, test_auc.mean(axis=1) - 2*test_auc.std(axis=1), test_auc.mean(axis=1) + 2*test_auc.std(axis=1), color='#888888', alpha=0.2)\n",
    "ax.legend(loc='best')\n",
    "ax.set_ylim([0.80,1.02])\n",
    "ax.set_ylabel(\"AUC\")\n",
    "ax.set_xlabel(\"Максимальная глубина\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Наилучшее значение AUC перекрестной проверки равно 0.963 и достигается при минимальном количестве наблюдений в листе, равном 3\n"
     ]
    }
   ],
   "source": [
    "# Создаем списки для сохранения AUC на обучающей и контрольной выборках\n",
    "train_auc = []\n",
    "test_auc = []\n",
    "temp_train_auc = []\n",
    "temp_test_auc = []\n",
    "min_samples_leaf_grid = [1, 3, 5, 7, 9, 11, 13, 15, 17, 20, 22, 24]\n",
    "\n",
    "# Строим модели с разным минимальным количеством наблюдений в листе\n",
    "for min_samples_leaf in min_samples_leaf_grid:\n",
    "    rf = RandomForestClassifier(n_estimators=300, random_state=42, n_jobs=-1, \n",
    "                                min_samples_leaf=min_samples_leaf)\n",
    "    temp_train_auc = []\n",
    "    temp_test_auc = []\n",
    "    for train_index, test_index in strat.split(X, y):\n",
    "        X_train, X_test = X.iloc[train_index], X.iloc[test_index]\n",
    "        y_train, y_test = y[train_index], y[test_index]\n",
    "        rf.fit(X_train, y_train)\n",
    "        temp_train_auc.append(roc_auc_score(y_train, rf.predict_proba(X_train)[:, 1]))\n",
    "        temp_test_auc.append(roc_auc_score(y_test, rf.predict_proba(X_test)[:, 1]))\n",
    "    train_auc.append(temp_train_auc)\n",
    "    test_auc.append(temp_test_auc)\n",
    "\n",
    "# Преобразуем списки в массивы NumPy\n",
    "train_auc, test_auc = np.asarray(train_auc), np.asarray(test_auc)\n",
    "print(\"Наилучшее значение AUC перекрестной проверки равно {:.3f} и достигается при минимальном количестве наблюдений в листе, равном {}\".\n",
    "      format(max(test_auc.mean(axis=1)), min_samples_leaf_grid[np.argmax(test_auc.mean(axis=1))]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1cc17890400>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VV18lKyvrqBMh9XIZ+5G6/CuvvJJ//vOfLFu2LGrfb7/91qjtbsmf//xnrFYr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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc12f85358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "ax.plot(min_samples_leaf_grid, train_auc.mean(axis=1), alpha=0.5, color='blue', label='обучение')\n",
    "ax.plot(min_samples_leaf_grid, test_auc.mean(axis=1), alpha=0.5, color='red', label='перекрестная проверка')\n",
    "ax.fill_between(min_samples_leaf_grid, test_auc.mean(axis=1) - test_auc.std(axis=1), test_auc.mean(axis=1) + test_auc.std(axis=1), color='#888888', alpha=0.4)\n",
    "ax.fill_between(min_samples_leaf_grid, test_auc.mean(axis=1) - 2*test_auc.std(axis=1), test_auc.mean(axis=1) + 2*test_auc.std(axis=1), color='#888888', alpha=0.2)\n",
    "ax.legend(loc='best')\n",
    "ax.set_ylim([0.88,1.02])\n",
    "ax.set_ylabel(\"AUC\")\n",
    "ax.set_xlabel(\"Минимальное количество наблюдений в листе\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Простой решетчатый поиск"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Размер обучающей выборки: 6219 размер контрольной выборки: 2074\n",
      "Наилучшее значение правильности: 0.93\n",
      "Наилучшие значения параметров: {'max_features': 12, 'max_depth': 20}\n"
     ]
    }
   ],
   "source": [
    "# реализация простого решетчатого поиска, метрика – правильность\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "X_train, X_control, y_train, y_control = train_test_split(X, y, random_state=42)\n",
    "print(\"Размер обучающей выборки: {} размер контрольной выборки: {}\".format(X_train.shape[0], X_control.shape[0]))\n",
    "\n",
    "best_score = 0\n",
    "\n",
    "for max_depth in [10, 12, 14, 16, 18, 20, 22]:\n",
    "    for max_features in [3, 6, 9, 12, 15, 18, 21]:\n",
    "        # для каждой комбинации параметров обучаем случайный лес\n",
    "        rf = RandomForestClassifier(max_depth=max_depth, max_features=max_features,  \n",
    "                                    n_estimators=300, n_jobs=-1, random_state=42)\n",
    "        rf.fit(X_train, y_train)\n",
    "        # оцениваем качество случайного леса на контрольной выборке\n",
    "        score = rf.score(X_control, y_control)\n",
    "        # если получаем наилучшее значение правильности, сохраняем значение и параметры\n",
    "        if score > best_score:\n",
    "            best_score = score\n",
    "            best_parameters = {'max_features': max_features, 'max_depth': max_depth}\n",
    "\n",
    "print(\"Наилучшее значение правильности: {:.2f}\".format(best_score))\n",
    "print(\"Наилучшие значения параметров: {}\".format(best_parameters))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Размер обучающей выборки: 6219 размер контрольной выборки: 2074\n",
      "Наилучшее значение AUC: 0.95\n",
      "Наилучшие значения параметров: {'max_features': 9, 'max_depth': 18}\n"
     ]
    }
   ],
   "source": [
    "# реализация простого решетчатого поиска, метрика – AUC\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "X_train, X_control, y_train, y_control = train_test_split(X, y, random_state=42)\n",
    "print(\"Размер обучающей выборки: {} размер контрольной выборки: {}\".format(X_train.shape[0], X_control.shape[0]))\n",
    "\n",
    "best_score = 0\n",
    "\n",
    "for max_depth in [10, 12, 14, 16, 18, 20, 22]:\n",
    "    for max_features in [3, 6, 9, 12, 15, 18, 21]:\n",
    "        # для каждой комбинации параметров обучаем случайный лес\n",
    "        rf = RandomForestClassifier(max_depth=max_depth, max_features=max_features,  \n",
    "                                    n_estimators=300, n_jobs=-1, random_state=42)\n",
    "        rf.fit(X_train, y_train)\n",
    "        # оцениваем качество случайного леса на контрольной выборке\n",
    "        auc_score = roc_auc_score(y_control, rf.predict_proba(X_control)[:, 1])\n",
    "        # если получаем наилучшее значение AUC, сохраняем значение и параметры\n",
    "        if auc_score > best_score:\n",
    "            best_score = auc_score\n",
    "            best_parameters = {'max_features': max_features, 'max_depth': max_depth}\n",
    "\n",
    "print(\"Наилучшее значение AUC: {:.2f}\".format(best_score))\n",
    "print(\"Наилучшие значения параметров: {}\".format(best_parameters))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Решетчатый поиск с комбинированной проверкой"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Размер обучающей выборки: 6219 размер тестовой выборки: 2074\n",
      "Лучшее усредненное значение AUC cv: 0.92\n",
      "Наилучшие значения параметров:  {'max_features': 9, 'max_depth': 14}\n",
      "AUC модели с наилучшими параметрами на тестовой выборке: 0.95\n"
     ]
    }
   ],
   "source": [
    "# разбиваем данные на обучающую и тестовую выборки\n",
    "X_trainval, X_test, y_trainval, y_test = train_test_split(X, y, random_state=42)\n",
    "print(\"Размер обучающей выборки: {} размер тестовой выборки: {}\".format(X_trainval.shape[0], X_test.shape[0]))\n",
    "\n",
    "best_score = 0\n",
    "\n",
    "for max_depth in [10, 12, 14, 16, 18, 20, 22]:\n",
    "    for max_features in [3, 6, 9, 12, 15, 18, 21]:\n",
    "        # для каждой комбинации параметров обучаем случайный лес\n",
    "        rf = RandomForestClassifier(max_depth=max_depth, max_features=max_features,  \n",
    "                                    n_estimators=300, n_jobs=-1, random_state=42)\n",
    "        # выполняем перекрестную проверку        \n",
    "        scores = cross_val_score(rf, X_trainval, y_trainval, scoring='roc_auc', cv=strat)\n",
    "        # вычисляем среднее значение AUC перекрестной проверки \n",
    "        auc_score = np.mean(scores)\n",
    "        # если получаем лучшее значение AUC, сохраняем его и параметры\n",
    "        if auc_score > best_score:\n",
    "            best_score = auc_score\n",
    "            best_parameters = {'max_features': max_features, 'max_depth': max_depth}\n",
    "# строим модель с параметрами, давшими наилучшее значение AUC на обучающей выборке, \n",
    "# и проверяем на тестовой выборке\n",
    "rf_best = RandomForestClassifier(**best_parameters, n_estimators=300, random_state=42)\n",
    "rf_best.fit(X_trainval, y_trainval)\n",
    "test_score = roc_auc_score(y_test, rf_best.predict_proba(X_test)[:, 1])\n",
    "print(\"Лучшее усредненное значение AUC cv: {:.2f}\".format(best_score))\n",
    "print(\"Наилучшие значения параметров: \", best_parameters)\n",
    "print(\"AUC модели с наилучшими параметрами на тестовой выборке: {:.2f}\".format(test_score))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Сетка параметров:\n",
      "{'max_features': [3, 6, 9, 12, 15, 18, 21], 'max_depth': [10, 12, 14, 16, 18, 20, 22]}\n"
     ]
    }
   ],
   "source": [
    "param_grid = {'max_features': [3, 6, 9, 12, 15, 18, 21],\n",
    "'max_depth': [10, 12, 14, 16, 18, 20, 22]}\n",
    "print(\"Сетка параметров:\\n{}\".format(param_grid))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "rf = RandomForestClassifier(n_estimators=300,random_state=42)\n",
    "grid_search = GridSearchCV(rf, param_grid, n_jobs=-1, cv=strat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=StratifiedKFold(n_splits=10, random_state=42, shuffle=True),\n",
       "       error_score='raise',\n",
       "       estimator=RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
       "            max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "            min_impurity_split=1e-07, min_samples_leaf=1,\n",
       "            min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "            n_estimators=300, n_jobs=1, oob_score=False, random_state=42,\n",
       "            verbose=0, warm_start=False),\n",
       "       fit_params={}, iid=True, n_jobs=-1,\n",
       "       param_grid={'max_features': [3, 6, 9, 12, 15, 18, 21], 'max_depth': [10, 12, 14, 16, 18, 20, 22]},\n",
       "       pre_dispatch='2*n_jobs', refit=True, return_train_score=True,\n",
       "       scoring=None, verbose=0)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Правильность на тестовой выборке: 0.92\n"
     ]
    }
   ],
   "source": [
    "print(\"Правильность на тестовой выборке: {:.2f}\".format(grid_search.score(X_test, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC на тестовой выборке: 0.95\n"
     ]
    }
   ],
   "source": [
    "grid_search2 = GridSearchCV(rf, param_grid, scoring='roc_auc', n_jobs=-1, cv=strat)\n",
    "grid_search2.fit(X_train, y_train)\n",
    "test_score = roc_auc_score(y_test, grid_search2.predict_proba(X_test)[:, 1])\n",
    "print(\"AUC на тестовой выборке: {:.2f}\".format(test_score))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Наилучшие значения параметров: {'max_features': 9, 'max_depth': 14}\n",
      "Наилучшее значение AUC: 0.92\n"
     ]
    }
   ],
   "source": [
    "print(\"Наилучшие значения параметров: {}\".format(grid_search2.best_params_))\n",
    "print(\"Наилучшее значение AUC: {:.2f}\".format(grid_search2.best_score_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Оптимальная модель:\n",
      "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
      "            max_depth=14, max_features=9, max_leaf_nodes=None,\n",
      "            min_impurity_split=1e-07, min_samples_leaf=1,\n",
      "            min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
      "            n_estimators=300, n_jobs=1, oob_score=False, random_state=42,\n",
      "            verbose=0, warm_start=False)\n"
     ]
    }
   ],
   "source": [
    "print(\"Оптимальная модель:\\n{}\".format(grid_search2.best_estimator_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>mean_train_score</th>\n",
       "      <th>param_max_depth</th>\n",
       "      <th>param_max_features</th>\n",
       "      <th>params</th>\n",
       "      <th>rank_test_score</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split0_train_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split1_train_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>split2_train_score</th>\n",
       "      <th>split3_test_score</th>\n",
       "      <th>split3_train_score</th>\n",
       "      <th>split4_test_score</th>\n",
       "      <th>split4_train_score</th>\n",
       "      <th>split5_test_score</th>\n",
       "      <th>split5_train_score</th>\n",
       "      <th>split6_test_score</th>\n",
       "      <th>split6_train_score</th>\n",
       "      <th>split7_test_score</th>\n",
       "      <th>split7_train_score</th>\n",
       "      <th>split8_test_score</th>\n",
       "      <th>split8_train_score</th>\n",
       "      <th>split9_test_score</th>\n",
       "      <th>split9_train_score</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>std_test_score</th>\n",
       "      <th>std_train_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.038978</td>\n",
       "      <td>0.181162</td>\n",
       "      <td>0.904436</td>\n",
       "      <td>0.988413</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>{'max_features': 3, 'max_depth': 10}</td>\n",
       "      <td>49</td>\n",
       "      <td>0.906963</td>\n",
       "      <td>0.988684</td>\n",
       "      <td>0.906524</td>\n",
       "      <td>0.987963</td>\n",
       "      <td>0.888652</td>\n",
       "      <td>0.988407</td>\n",
       "      <td>0.885369</td>\n",
       "      <td>0.988640</td>\n",
       "      <td>0.919844</td>\n",
       "      <td>0.988635</td>\n",
       "      <td>0.891835</td>\n",
       "      <td>0.989159</td>\n",
       "      <td>0.936146</td>\n",
       "      <td>0.987206</td>\n",
       "      <td>0.899726</td>\n",
       "      <td>0.989036</td>\n",
       "      <td>0.918574</td>\n",
       "      <td>0.988622</td>\n",
       "      <td>0.890720</td>\n",
       "      <td>0.987777</td>\n",
       "      <td>0.501293</td>\n",
       "      <td>0.049010</td>\n",
       "      <td>0.015605</td>\n",
       "      <td>0.000568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.015017</td>\n",
       "      <td>0.166919</td>\n",
       "      <td>0.912527</td>\n",
       "      <td>0.989677</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>{'max_features': 6, 'max_depth': 10}</td>\n",
       "      <td>43</td>\n",
       "      <td>0.918090</td>\n",
       "      <td>0.989930</td>\n",
       "      <td>0.917785</td>\n",
       "      <td>0.989007</td>\n",
       "      <td>0.908583</td>\n",
       "      <td>0.990678</td>\n",
       "      <td>0.886319</td>\n",
       "      <td>0.989686</td>\n",
       "      <td>0.930760</td>\n",
       "      <td>0.989431</td>\n",
       "      <td>0.893736</td>\n",
       "      <td>0.990134</td>\n",
       "      <td>0.941849</td>\n",
       "      <td>0.988974</td>\n",
       "      <td>0.908828</td>\n",
       "      <td>0.989570</td>\n",
       "      <td>0.922848</td>\n",
       "      <td>0.990150</td>\n",
       "      <td>0.896458</td>\n",
       "      <td>0.989203</td>\n",
       "      <td>0.165205</td>\n",
       "      <td>0.027373</td>\n",
       "      <td>0.016385</td>\n",
       "      <td>0.000523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6.040694</td>\n",
       "      <td>0.145403</td>\n",
       "      <td>0.914460</td>\n",
       "      <td>0.990099</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>{'max_features': 9, 'max_depth': 10}</td>\n",
       "      <td>41</td>\n",
       "      <td>0.920074</td>\n",
       "      <td>0.990447</td>\n",
       "      <td>0.920320</td>\n",
       "      <td>0.989489</td>\n",
       "      <td>0.917224</td>\n",
       "      <td>0.991099</td>\n",
       "      <td>0.878773</td>\n",
       "      <td>0.989919</td>\n",
       "      <td>0.939286</td>\n",
       "      <td>0.989941</td>\n",
       "      <td>0.893131</td>\n",
       "      <td>0.990364</td>\n",
       "      <td>0.941763</td>\n",
       "      <td>0.989155</td>\n",
       "      <td>0.908972</td>\n",
       "      <td>0.990677</td>\n",
       "      <td>0.926771</td>\n",
       "      <td>0.990438</td>\n",
       "      <td>0.898273</td>\n",
       "      <td>0.989461</td>\n",
       "      <td>0.219647</td>\n",
       "      <td>0.018977</td>\n",
       "      <td>0.018993</td>\n",
       "      <td>0.000580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.933347</td>\n",
       "      <td>0.156866</td>\n",
       "      <td>0.911911</td>\n",
       "      <td>0.990113</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>{'max_features': 12, 'max_depth': 10}</td>\n",
       "      <td>44</td>\n",
       "      <td>0.914381</td>\n",
       "      <td>0.990351</td>\n",
       "      <td>0.924813</td>\n",
       "      <td>0.989873</td>\n",
       "      <td>0.916878</td>\n",
       "      <td>0.991217</td>\n",
       "      <td>0.879752</td>\n",
       "      <td>0.989687</td>\n",
       "      <td>0.933669</td>\n",
       "      <td>0.989993</td>\n",
       "      <td>0.886478</td>\n",
       "      <td>0.990351</td>\n",
       "      <td>0.938767</td>\n",
       "      <td>0.989275</td>\n",
       "      <td>0.903067</td>\n",
       "      <td>0.990775</td>\n",
       "      <td>0.926976</td>\n",
       "      <td>0.990284</td>\n",
       "      <td>0.894321</td>\n",
       "      <td>0.989322</td>\n",
       "      <td>0.327755</td>\n",
       "      <td>0.018698</td>\n",
       "      <td>0.019202</td>\n",
       "      <td>0.000581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8.291801</td>\n",
       "      <td>0.137649</td>\n",
       "      <td>0.911697</td>\n",
       "      <td>0.990166</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>{'max_features': 15, 'max_depth': 10}</td>\n",
       "      <td>45</td>\n",
       "      <td>0.916451</td>\n",
       "      <td>0.990766</td>\n",
       "      <td>0.929421</td>\n",
       "      <td>0.989754</td>\n",
       "      <td>0.906740</td>\n",
       "      <td>0.990969</td>\n",
       "      <td>0.878600</td>\n",
       "      <td>0.989941</td>\n",
       "      <td>0.938335</td>\n",
       "      <td>0.990353</td>\n",
       "      <td>0.884001</td>\n",
       "      <td>0.990615</td>\n",
       "      <td>0.938767</td>\n",
       "      <td>0.989302</td>\n",
       "      <td>0.905573</td>\n",
       "      <td>0.990579</td>\n",
       "      <td>0.927035</td>\n",
       "      <td>0.990076</td>\n",
       "      <td>0.892037</td>\n",
       "      <td>0.989308</td>\n",
       "      <td>0.745365</td>\n",
       "      <td>0.036146</td>\n",
       "      <td>0.020797</td>\n",
       "      <td>0.000559</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_fit_time  mean_score_time  mean_test_score  mean_train_score  \\\n",
       "0       4.038978         0.181162         0.904436          0.988413   \n",
       "1       5.015017         0.166919         0.912527          0.989677   \n",
       "2       6.040694         0.145403         0.914460          0.990099   \n",
       "3       7.933347         0.156866         0.911911          0.990113   \n",
       "4       8.291801         0.137649         0.911697          0.990166   \n",
       "\n",
       "  param_max_depth param_max_features                                 params  \\\n",
       "0              10                  3   {'max_features': 3, 'max_depth': 10}   \n",
       "1              10                  6   {'max_features': 6, 'max_depth': 10}   \n",
       "2              10                  9   {'max_features': 9, 'max_depth': 10}   \n",
       "3              10                 12  {'max_features': 12, 'max_depth': 10}   \n",
       "4              10                 15  {'max_features': 15, 'max_depth': 10}   \n",
       "\n",
       "   rank_test_score  split0_test_score  split0_train_score  split1_test_score  \\\n",
       "0               49           0.906963            0.988684           0.906524   \n",
       "1               43           0.918090            0.989930           0.917785   \n",
       "2               41           0.920074            0.990447           0.920320   \n",
       "3               44           0.914381            0.990351           0.924813   \n",
       "4               45           0.916451            0.990766           0.929421   \n",
       "\n",
       "   split1_train_score  split2_test_score  split2_train_score  \\\n",
       "0            0.987963           0.888652            0.988407   \n",
       "1            0.989007           0.908583            0.990678   \n",
       "2            0.989489           0.917224            0.991099   \n",
       "3            0.989873           0.916878            0.991217   \n",
       "4            0.989754           0.906740            0.990969   \n",
       "\n",
       "   split3_test_score  split3_train_score  split4_test_score  \\\n",
       "0           0.885369            0.988640           0.919844   \n",
       "1           0.886319            0.989686           0.930760   \n",
       "2           0.878773            0.989919           0.939286   \n",
       "3           0.879752            0.989687           0.933669   \n",
       "4           0.878600            0.989941           0.938335   \n",
       "\n",
       "   split4_train_score  split5_test_score  split5_train_score  \\\n",
       "0            0.988635           0.891835            0.989159   \n",
       "1            0.989431           0.893736            0.990134   \n",
       "2            0.989941           0.893131            0.990364   \n",
       "3            0.989993           0.886478            0.990351   \n",
       "4            0.990353           0.884001            0.990615   \n",
       "\n",
       "   split6_test_score  split6_train_score  split7_test_score  \\\n",
       "0           0.936146            0.987206           0.899726   \n",
       "1           0.941849            0.988974           0.908828   \n",
       "2           0.941763            0.989155           0.908972   \n",
       "3           0.938767            0.989275           0.903067   \n",
       "4           0.938767            0.989302           0.905573   \n",
       "\n",
       "   split7_train_score  split8_test_score  split8_train_score  \\\n",
       "0            0.989036           0.918574            0.988622   \n",
       "1            0.989570           0.922848            0.990150   \n",
       "2            0.990677           0.926771            0.990438   \n",
       "3            0.990775           0.926976            0.990284   \n",
       "4            0.990579           0.927035            0.990076   \n",
       "\n",
       "   split9_test_score  split9_train_score  std_fit_time  std_score_time  \\\n",
       "0           0.890720            0.987777      0.501293        0.049010   \n",
       "1           0.896458            0.989203      0.165205        0.027373   \n",
       "2           0.898273            0.989461      0.219647        0.018977   \n",
       "3           0.894321            0.989322      0.327755        0.018698   \n",
       "4           0.892037            0.989308      0.745365        0.036146   \n",
       "\n",
       "   std_test_score  std_train_score  \n",
       "0        0.015605         0.000568  \n",
       "1        0.016385         0.000523  \n",
       "2        0.018993         0.000580  \n",
       "3        0.019202         0.000581  \n",
       "4        0.020797         0.000559  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "# преобразуем в DataFrame\n",
    "results = pd.DataFrame(grid_search2.cv_results_)\n",
    "# показываем первые 5 строк\n",
    "display(results.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                    mean_test_score\n",
      "param_max_depth param_max_features                 \n",
      "10              3                          0.904436\n",
      "                6                          0.912527\n",
      "                9                          0.914460\n",
      "                12                         0.911911\n",
      "                15                         0.911697\n",
      "                18                         0.911046\n",
      "                21                         0.908961\n",
      "12              3                          0.914898\n",
      "                6                          0.920171\n",
      "                9                          0.919679\n",
      "                12                         0.921322\n",
      "                15                         0.918294\n",
      "                18                         0.920597\n",
      "                21                         0.917767\n",
      "14              3                          0.916738\n",
      "                6                          0.921421\n",
      "                9                          0.922605\n",
      "                12                         0.922367\n",
      "                15                         0.921367\n",
      "                18                         0.922160\n",
      "                21                         0.919614\n",
      "16              3                          0.915798\n",
      "                6                          0.920416\n",
      "                9                          0.919954\n",
      "                12                         0.918770\n",
      "                15                         0.919831\n",
      "                18                         0.920081\n",
      "                21                         0.917971\n",
      "18              3                          0.915460\n",
      "                6                          0.919177\n",
      "                9                          0.918210\n",
      "                12                         0.919541\n",
      "                15                         0.920100\n",
      "                18                         0.918639\n",
      "                21                         0.919199\n",
      "20              3                          0.914086\n",
      "                6                          0.918086\n",
      "                9                          0.917643\n",
      "                12                         0.917725\n",
      "                15                         0.917690\n",
      "                18                         0.917456\n",
      "                21                         0.918291\n",
      "22              3                          0.911623\n",
      "                6                          0.916669\n",
      "                9                          0.916364\n",
      "                12                         0.917406\n",
      "                15                         0.916890\n",
      "                18                         0.919433\n",
      "                21                         0.917613\n"
     ]
    }
   ],
   "source": [
    "table = results.pivot_table(values=[\"mean_test_score\"],    \n",
    "                            index=[\"param_max_depth\",\"param_max_features\"])\n",
    "print(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PolyCollection at 0x1cc176c2470>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5zcw9rvh3h4sV/y1z7+C7jFQ+ST5yftpNt7M1N5N3j+5v1T5crWHn/HuYtfZz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\n3nXiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc176c5ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# пишем функцию, которая будет строить теплокарту усредненных значений AUC\n",
    "def heatmap(values, xlabel, ylabel, xticklabels, yticklabels, cmap=None,\n",
    "            vmin=None, vmax=None, ax=None, fmt=\"%0.2f\"):\n",
    "    if ax is None:\n",
    "        ax = plt.gca()\n",
    "    img = ax.pcolor(values, cmap=cmap, vmin=None, vmax=None)\n",
    "    img.update_scalarmappable()\n",
    "    ax.set_xlabel(xlabel)\n",
    "    ax.set_ylabel(ylabel)\n",
    "    ax.set_xticks(np.arange(len(xticklabels)) + .7)\n",
    "    ax.set_yticks(np.arange(len(yticklabels)) + .7)\n",
    "    ax.set_xticklabels(xticklabels)\n",
    "    ax.set_yticklabels(yticklabels)\n",
    "    ax.set_aspect(1)\n",
    "\n",
    "    for p, color, value in zip(img.get_paths(), img.get_facecolors(),\n",
    "                               img.get_array()):\n",
    "        x, y = p.vertices[:-2, :].mean(0)\n",
    "        if np.mean(color[:3]) > 0.5:\n",
    "            c = 'k'\n",
    "        else:\n",
    "            c = 'w'\n",
    "        ax.text(x, y, fmt % value, color=c, ha=\"center\", va=\"center\")\n",
    "    return img\n",
    "\n",
    "# создаем массив усредненных значений AUC\n",
    "scores = np.array(results.mean_test_score).reshape(7, 7)\n",
    "# строим теплокарту на основе усредненных значений AUC\n",
    "heatmap(scores, xlabel='max_features', xticklabels=param_grid['max_features'],\n",
    "                      ylabel='max_depth', yticklabels=param_grid['max_depth'], cmap=\"viridis\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC на обучающей выборке: 1.000\n",
      "AUC на контрольной выборке: 0.869\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "extratrees = ExtraTreesClassifier(random_state=42)\n",
    "extratrees.fit(X_train, y_train)\n",
    "print(\"AUC на обучающей выборке: {:.3f}\".\n",
    "      format(roc_auc_score(y_train, extratrees.predict_proba(X_train)[:, 1])))\n",
    "print(\"AUC на контрольной выборке: {:.3f}\".\n",
    "      format(roc_auc_score(y_test, extratrees.predict_proba(X_test)[:, 1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Наилучшее значение AUC: 0.90\n",
      "Наилучшие значения параметров: {'max_features': 9, 'max_depth': 14}\n",
      "AUC на тестовой выборке: 0.92\n"
     ]
    }
   ],
   "source": [
    "extratrees2 = ExtraTreesClassifier(n_estimators=400, random_state=42)\n",
    "param_grid = {'max_features': [3, 6, 9, 12, 15, 18, 21],\n",
    "              'max_depth': [10, 12, 14, 16, 18, 20, 22]}\n",
    "grid_search3 = GridSearchCV(extratrees2, param_grid, scoring='roc_auc', n_jobs=-1, cv=strat)\n",
    "grid_search3.fit(X_train, y_train)\n",
    "test_score = roc_auc_score(y_test, grid_search3.predict_proba(X_test)[:, 1])\n",
    "print(\"Наилучшее значение AUC: {:.2f}\".format(grid_search3.best_score_))\n",
    "print(\"Наилучшие значения параметров: {}\".format(grid_search3.best_params_))\n",
    "print(\"AUC на тестовой выборке: {:.2f}\".format(test_score))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Построение распределенного случайного леса с помощью класса H2ORandomForestEstimator"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Подготовка данных для построения стандартной модели случайного леса"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>client_id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>job_position</th>\n",
       "      <th>credit_sum</th>\n",
       "      <th>credit_month</th>\n",
       "      <th>score_shk</th>\n",
       "      <th>education</th>\n",
       "      <th>tariff_id</th>\n",
       "      <th>living_region</th>\n",
       "      <th>okrug</th>\n",
       "      <th>avregzarplata</th>\n",
       "      <th>monthly_income</th>\n",
       "      <th>credit_count</th>\n",
       "      <th>overdue_credit_count</th>\n",
       "      <th>open_account_flg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>2.0</td>\n",
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       "      <th>2</th>\n",
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       "      <td>27.0</td>\n",
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       "      <td>12009,09</td>\n",
       "      <td>12</td>\n",
       "      <td>0,362536</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23650.0</td>\n",
       "      <td>17000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>6.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   client_id  gender   age  marital_status  job_position credit_sum  \\\n",
       "0          1       2  48.0             3.0            15      59998   \n",
       "1          2       1  28.0             NaN            15      10889   \n",
       "2          3       2  32.0             3.0            14      10728   \n",
       "3          4       1  27.0             2.0            14   12009,09   \n",
       "4          5       2  45.0             3.0            14   16908,89   \n",
       "\n",
       "   credit_month score_shk  education  tariff_id  living_region  okrug  \\\n",
       "0            10  0,770249        2.0         28           23.0    8.0   \n",
       "1             6  0,248514        2.0          2           30.0    7.0   \n",
       "2            12  0,459589        4.0          2           64.0    2.0   \n",
       "3            12  0,362536        2.0          2            8.0    8.0   \n",
       "4            10  0,421385        4.0          2           77.0    6.0   \n",
       "\n",
       "   avregzarplata  monthly_income  credit_count  overdue_credit_count  \\\n",
       "0        25850.0         30000.0           1.0                   1.0   \n",
       "1        66880.0         43000.0           2.0                   0.0   \n",
       "2        23430.0         23000.0           5.0                   0.0   \n",
       "3        23650.0         17000.0           2.0                   0.0   \n",
       "4        26620.0             NaN           1.0                   0.0   \n",
       "\n",
       "   open_account_flg  \n",
       "0                 0  \n",
       "1                 0  \n",
       "2                 0  \n",
       "3                 0  \n",
       "4                 0  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"C:/Trees/Credit.csv\", encoding='cp1251', sep=';')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "del data['client_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 170746 entries, 0 to 170745\n",
      "Data columns (total 16 columns):\n",
      "gender                  170746 non-null int64\n",
      "age                     170744 non-null float64\n",
      "marital_status          170741 non-null float64\n",
      "job_position            170746 non-null int64\n",
      "credit_sum              170745 non-null object\n",
      "credit_month            170746 non-null int64\n",
      "score_shk               170743 non-null object\n",
      "education               170743 non-null float64\n",
      "tariff_id               170746 non-null int64\n",
      "living_region           170554 non-null float64\n",
      "okrug                   170554 non-null float64\n",
      "avregzarplata           170554 non-null float64\n",
      "monthly_income          170744 non-null float64\n",
      "credit_count            161516 non-null float64\n",
      "overdue_credit_count    161516 non-null float64\n",
      "open_account_flg        170746 non-null int64\n",
      "dtypes: float64(9), int64(5), object(2)\n",
      "memory usage: 20.8+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(data.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in ['gender', 'marital_status', 'job_position', 'education', \n",
    "          'tariff_id', 'living_region', 'okrug', 'open_account_flg']:\n",
    "    if i in data.columns:\n",
    "        data[i]=data[i].astype('str')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data['credit_sum'] = data['credit_sum'].str.replace(',', '.')\n",
    "data['score_shk'] = data['score_shk'].str.replace(',', '.')\n",
    "data['credit_sum'] = data['credit_sum'].astype('float')\n",
    "data['score_shk'] = data['score_shk'].astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 170746 entries, 0 to 170745\n",
      "Data columns (total 16 columns):\n",
      "gender                  170746 non-null object\n",
      "age                     170744 non-null float64\n",
      "marital_status          170746 non-null object\n",
      "job_position            170746 non-null object\n",
      "credit_sum              170745 non-null float64\n",
      "credit_month            170746 non-null int64\n",
      "score_shk               170743 non-null float64\n",
      "education               170746 non-null object\n",
      "tariff_id               170746 non-null object\n",
      "living_region           170746 non-null object\n",
      "okrug                   170746 non-null object\n",
      "avregzarplata           170554 non-null float64\n",
      "monthly_income          170744 non-null float64\n",
      "credit_count            161516 non-null float64\n",
      "overdue_credit_count    161516 non-null float64\n",
      "open_account_flg        170746 non-null object\n",
      "dtypes: float64(7), int64(1), object(8)\n",
      "memory usage: 20.8+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(data.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
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       "      <td>6</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>32.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
       "      <td>10728.00</td>\n",
       "      <td>12</td>\n",
       "      <td>0.459589</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>64.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23430.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>27.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>14</td>\n",
       "      <td>12009.09</td>\n",
       "      <td>12</td>\n",
       "      <td>0.362536</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23650.0</td>\n",
       "      <td>17000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>45.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
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       "      <td>10</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>77.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>26620.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  gender   age marital_status job_position  credit_sum  credit_month  \\\n",
       "0      2  48.0            3.0           15    59998.00            10   \n",
       "1      1  28.0            nan           15    10889.00             6   \n",
       "2      2  32.0            3.0           14    10728.00            12   \n",
       "3      1  27.0            2.0           14    12009.09            12   \n",
       "4      2  45.0            3.0           14    16908.89            10   \n",
       "\n",
       "   score_shk education tariff_id living_region okrug  avregzarplata  \\\n",
       "0   0.770249       2.0        28          23.0   8.0        25850.0   \n",
       "1   0.248514       2.0         2          30.0   7.0        66880.0   \n",
       "2   0.459589       4.0         2          64.0   2.0        23430.0   \n",
       "3   0.362536       2.0         2           8.0   8.0        23650.0   \n",
       "4   0.421385       4.0         2          77.0   6.0        26620.0   \n",
       "\n",
       "   monthly_income  credit_count  overdue_credit_count open_account_flg  \n",
       "0         30000.0           1.0                   1.0                0  \n",
       "1         43000.0           2.0                   0.0                0  \n",
       "2         23000.0           5.0                   0.0                0  \n",
       "3         17000.0           2.0                   0.0                0  \n",
       "4             NaN           1.0                   0.0                0  "
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1    88697\n",
      "2    82049\n",
      "Name: gender, dtype: int64\n",
      "3.0    93952\n",
      "4.0    52148\n",
      "2.0    16970\n",
      "1.0     4196\n",
      "5.0     3475\n",
      "nan        5\n",
      "Name: marital_status, dtype: int64\n",
      "14    134680\n",
      "15     17674\n",
      "2       5591\n",
      "10      4107\n",
      "4       3750\n",
      "1       2791\n",
      "17       656\n",
      "8        537\n",
      "16       352\n",
      "6        241\n",
      "3        126\n",
      "18       110\n",
      "11        65\n",
      "13        40\n",
      "12        12\n",
      "5          8\n",
      "7          5\n",
      "9          1\n",
      "Name: job_position, dtype: int64\n",
      "4.0    87537\n",
      "2.0    72593\n",
      "5.0     9941\n",
      "3.0      565\n",
      "1.0      107\n",
      "nan        3\n",
      "Name: education, dtype: int64\n",
      "2     69355\n",
      "28    39117\n",
      "19    15537\n",
      "20    10970\n",
      "25     7497\n",
      "30     5538\n",
      "22     3930\n",
      "18     3339\n",
      "3      3232\n",
      "1      2245\n",
      "23     2228\n",
      "6      2102\n",
      "29     1007\n",
      "8       766\n",
      "4       717\n",
      "9       579\n",
      "7       540\n",
      "32      414\n",
      "10      376\n",
      "11      370\n",
      "31      317\n",
      "12      303\n",
      "21      132\n",
      "13       56\n",
      "5        36\n",
      "14       11\n",
      "16       10\n",
      "26        7\n",
      "15        6\n",
      "24        5\n",
      "27        2\n",
      "17        1\n",
      "33        1\n",
      "Name: tariff_id, dtype: int64\n",
      "31.0    12844\n",
      "30.0     9261\n",
      "73.0     8735\n",
      "23.0     8355\n",
      "63.0     8303\n",
      "57.0     7667\n",
      "66.0     7316\n",
      "46.0     6466\n",
      "77.0     5155\n",
      "62.0     5104\n",
      "68.0     4617\n",
      "60.0     4328\n",
      "14.0     4323\n",
      "33.0     3695\n",
      "40.0     3614\n",
      "27.0     3529\n",
      "24.0     3121\n",
      "20.0     2890\n",
      "4.0      2719\n",
      "9.0      2605\n",
      "8.0      2293\n",
      "64.0     2282\n",
      "35.0     2169\n",
      "3.0      1895\n",
      "52.0     1860\n",
      "55.0     1857\n",
      "10.0     1723\n",
      "47.0     1643\n",
      "76.0     1560\n",
      "70.0     1548\n",
      "        ...  \n",
      "38.0      748\n",
      "34.0      745\n",
      "61.0      728\n",
      "16.0      728\n",
      "54.0      717\n",
      "65.0      705\n",
      "53.0      700\n",
      "51.0      679\n",
      "21.0      647\n",
      "15.0      637\n",
      "71.0      626\n",
      "19.0      576\n",
      "43.0      575\n",
      "58.0      564\n",
      "44.0      554\n",
      "1.0       553\n",
      "22.0      514\n",
      "59.0      480\n",
      "18.0      412\n",
      "56.0      379\n",
      "50.0      305\n",
      "11.0      203\n",
      "nan       192\n",
      "29.0      159\n",
      "48.0       69\n",
      "45.0       54\n",
      "81.0       32\n",
      "78.0       31\n",
      "49.0       19\n",
      "79.0       17\n",
      "Name: living_region, Length: 82, dtype: int64\n",
      "7.0    39049\n",
      "2.0    36092\n",
      "6.0    22552\n",
      "3.0    22303\n",
      "5.0    18602\n",
      "8.0    18554\n",
      "1.0     7074\n",
      "4.0     6328\n",
      "nan      192\n",
      "Name: okrug, dtype: int64\n",
      "0    140690\n",
      "1     30056\n",
      "Name: open_account_flg, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "categorical_columns = [c for c in data.columns if data[c].dtype.name == 'object']\n",
    "for c in categorical_columns:\n",
    "    print(data[c].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data.at[data['job_position'] == '5', 'job_position'] = '99'\n",
    "data.at[data['job_position'] == '7', 'job_position'] = '99'\n",
    "data.at[data['job_position'] == '9', 'job_position'] = '99'\n",
    "data.at[data['job_position'] == '12', 'job_position'] = '99'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14    134680\n",
      "15     17674\n",
      "2       5591\n",
      "10      4107\n",
      "4       3750\n",
      "1       2791\n",
      "17       656\n",
      "8        537\n",
      "16       352\n",
      "6        241\n",
      "3        126\n",
      "18       110\n",
      "11        65\n",
      "13        40\n",
      "99        26\n",
      "Name: job_position, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(data['job_position'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data.at[data['tariff_id'] == '14', 'tariff_id'] = '99'\n",
    "data.at[data['tariff_id'] == '15', 'tariff_id'] = '99'\n",
    "data.at[data['tariff_id'] == '16', 'tariff_id'] = '99'\n",
    "data.at[data['tariff_id'] == '17', 'tariff_id'] = '99'\n",
    "data.at[data['tariff_id'] == '24', 'tariff_id'] = '99'\n",
    "data.at[data['tariff_id'] == '26', 'tariff_id'] = '99'\n",
    "data.at[data['tariff_id'] == '27', 'tariff_id'] = '99'\n",
    "data.at[data['tariff_id'] == '33', 'tariff_id'] = '99'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2     69355\n",
      "28    39117\n",
      "19    15537\n",
      "20    10970\n",
      "25     7497\n",
      "30     5538\n",
      "22     3930\n",
      "18     3339\n",
      "3      3232\n",
      "1      2245\n",
      "23     2228\n",
      "6      2102\n",
      "29     1007\n",
      "8       766\n",
      "4       717\n",
      "9       579\n",
      "7       540\n",
      "32      414\n",
      "10      376\n",
      "11      370\n",
      "31      317\n",
      "12      303\n",
      "21      132\n",
      "13       56\n",
      "99       43\n",
      "5        36\n",
      "Name: tariff_id, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(data['tariff_id'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train=data.sample(frac=0.7,random_state=200)\n",
    "test=data.drop(train.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 119522 entries, 53397 to 149270\n",
      "Data columns (total 16 columns):\n",
      "gender                  119522 non-null object\n",
      "age                     119520 non-null float64\n",
      "marital_status          119522 non-null object\n",
      "job_position            119522 non-null object\n",
      "credit_sum              119522 non-null float64\n",
      "credit_month            119522 non-null int64\n",
      "score_shk               119519 non-null float64\n",
      "education               119522 non-null object\n",
      "tariff_id               119522 non-null object\n",
      "living_region           119522 non-null object\n",
      "okrug                   119522 non-null object\n",
      "avregzarplata           119383 non-null float64\n",
      "monthly_income          119521 non-null float64\n",
      "credit_count            113045 non-null float64\n",
      "overdue_credit_count    113045 non-null float64\n",
      "open_account_flg        119522 non-null object\n",
      "dtypes: float64(7), int64(1), object(8)\n",
      "memory usage: 15.5+ MB\n",
      "None\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 51224 entries, 0 to 170745\n",
      "Data columns (total 16 columns):\n",
      "gender                  51224 non-null object\n",
      "age                     51224 non-null float64\n",
      "marital_status          51224 non-null object\n",
      "job_position            51224 non-null object\n",
      "credit_sum              51223 non-null float64\n",
      "credit_month            51224 non-null int64\n",
      "score_shk               51224 non-null float64\n",
      "education               51224 non-null object\n",
      "tariff_id               51224 non-null object\n",
      "living_region           51224 non-null object\n",
      "okrug                   51224 non-null object\n",
      "avregzarplata           51171 non-null float64\n",
      "monthly_income          51223 non-null float64\n",
      "credit_count            48471 non-null float64\n",
      "overdue_credit_count    48471 non-null float64\n",
      "open_account_flg        51224 non-null object\n",
      "dtypes: float64(7), int64(1), object(8)\n",
      "memory usage: 6.6+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(train.info())\n",
    "print(test.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in ['age', 'credit_sum', 'score_shk', 'monthly_income']:\n",
    "    if i in train.columns:\n",
    "        train[i].fillna(train[i].median(), inplace=True)\n",
    "\n",
    "for i in ['age', 'credit_sum', 'score_shk', 'monthly_income']:\n",
    "    if i in test.columns:\n",
    "        test[i].fillna(test[i].median(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in ['avregzarplata', 'credit_count', 'overdue_credit_count']:\n",
    "    if i in train.columns:\n",
    "        train[i].fillna(-1, inplace=True)\n",
    "\n",
    "for i in ['avregzarplata', 'credit_count', 'overdue_credit_count']:\n",
    "    if i in test.columns:\n",
    "        test[i].fillna(-1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.0    65650\n",
      "4.0    36580\n",
      "2.0    11919\n",
      "1.0     2942\n",
      "5.0     2428\n",
      "nan        3\n",
      "Name: marital_status, dtype: int64\n",
      "3.0    28302\n",
      "4.0    15568\n",
      "2.0     5051\n",
      "1.0     1254\n",
      "5.0     1047\n",
      "nan        2\n",
      "Name: marital_status, dtype: int64\n",
      "4.0    61126\n",
      "2.0    50928\n",
      "5.0     6973\n",
      "3.0      418\n",
      "1.0       75\n",
      "nan        2\n",
      "Name: education, dtype: int64\n",
      "4.0    26411\n",
      "2.0    21665\n",
      "5.0     2968\n",
      "3.0      147\n",
      "1.0       32\n",
      "nan        1\n",
      "Name: education, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(train['marital_status'].value_counts())\n",
    "print(test['marital_status'].value_counts())\n",
    "\n",
    "print(train['education'].value_counts())\n",
    "print(test['education'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.at[train['marital_status'] == 'nan', 'marital_status'] = '3.0'\n",
    "test.at[test['marital_status'] == 'nan', 'marital_status'] = '3.0'\n",
    "\n",
    "train.at[train['education'] == 'nan', 'education'] = '4.0'\n",
    "test.at[test['education'] == 'nan', 'education'] = '4.0'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.0    65653\n",
      "4.0    36580\n",
      "2.0    11919\n",
      "1.0     2942\n",
      "5.0     2428\n",
      "Name: marital_status, dtype: int64\n",
      "3.0    28304\n",
      "4.0    15568\n",
      "2.0     5051\n",
      "1.0     1254\n",
      "5.0     1047\n",
      "Name: marital_status, dtype: int64\n",
      "4.0    61128\n",
      "2.0    50928\n",
      "5.0     6973\n",
      "3.0      418\n",
      "1.0       75\n",
      "Name: education, dtype: int64\n",
      "4.0    26412\n",
      "2.0    21665\n",
      "5.0     2968\n",
      "3.0      147\n",
      "1.0       32\n",
      "Name: education, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(train['marital_status'].value_counts())\n",
    "print(test['marital_status'].value_counts())\n",
    "\n",
    "print(train['education'].value_counts())\n",
    "print(test['education'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.at[train['living_region'] == 'nan', 'living_region'] = '99'\n",
    "test.at[test['living_region'] == 'nan', 'living_region'] = '99'\n",
    "\n",
    "train.at[train['okrug'] == 'nan', 'okrug'] = '99'\n",
    "test.at[test['okrug'] == 'nan', 'okrug'] = '99'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 119522 entries, 53397 to 149270\n",
      "Data columns (total 16 columns):\n",
      "gender                  119522 non-null object\n",
      "age                     119522 non-null float64\n",
      "marital_status          119522 non-null object\n",
      "job_position            119522 non-null object\n",
      "credit_sum              119522 non-null float64\n",
      "credit_month            119522 non-null int64\n",
      "score_shk               119522 non-null float64\n",
      "education               119522 non-null object\n",
      "tariff_id               119522 non-null object\n",
      "living_region           119522 non-null object\n",
      "okrug                   119522 non-null object\n",
      "avregzarplata           119522 non-null float64\n",
      "monthly_income          119522 non-null float64\n",
      "credit_count            119522 non-null float64\n",
      "overdue_credit_count    119522 non-null float64\n",
      "open_account_flg        119522 non-null object\n",
      "dtypes: float64(7), int64(1), object(8)\n",
      "memory usage: 15.5+ MB\n",
      "None\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 51224 entries, 0 to 170745\n",
      "Data columns (total 16 columns):\n",
      "gender                  51224 non-null object\n",
      "age                     51224 non-null float64\n",
      "marital_status          51224 non-null object\n",
      "job_position            51224 non-null object\n",
      "credit_sum              51224 non-null float64\n",
      "credit_month            51224 non-null int64\n",
      "score_shk               51224 non-null float64\n",
      "education               51224 non-null object\n",
      "tariff_id               51224 non-null object\n",
      "living_region           51224 non-null object\n",
      "okrug                   51224 non-null object\n",
      "avregzarplata           51224 non-null float64\n",
      "monthly_income          51224 non-null float64\n",
      "credit_count            51224 non-null float64\n",
      "overdue_credit_count    51224 non-null float64\n",
      "open_account_flg        51224 non-null object\n",
      "dtypes: float64(7), int64(1), object(8)\n",
      "memory usage: 6.6+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(train.info())\n",
    "print(test.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Исходные переменные:\n",
      " ['gender', 'age', 'marital_status', 'job_position', 'credit_sum', 'credit_month', 'score_shk', 'education', 'tariff_id', 'living_region', 'okrug', 'avregzarplata', 'monthly_income', 'credit_count', 'overdue_credit_count', 'open_account_flg'] \n",
      "\n",
      "Переменные после get_dummies:\n",
      " ['age', 'credit_sum', 'credit_month', 'score_shk', 'avregzarplata', 'monthly_income', 'credit_count', 'overdue_credit_count', 'gender_1', 'gender_2', 'marital_status_1.0', 'marital_status_2.0', 'marital_status_3.0', 'marital_status_4.0', 'marital_status_5.0', 'job_position_1', 'job_position_10', 'job_position_11', 'job_position_13', 'job_position_14', 'job_position_15', 'job_position_16', 'job_position_17', 'job_position_18', 'job_position_2', 'job_position_3', 'job_position_4', 'job_position_6', 'job_position_8', 'job_position_99', 'education_1.0', 'education_2.0', 'education_3.0', 'education_4.0', 'education_5.0', 'tariff_id_1', 'tariff_id_10', 'tariff_id_11', 'tariff_id_12', 'tariff_id_13', 'tariff_id_18', 'tariff_id_19', 'tariff_id_2', 'tariff_id_20', 'tariff_id_21', 'tariff_id_22', 'tariff_id_23', 'tariff_id_25', 'tariff_id_28', 'tariff_id_29', 'tariff_id_3', 'tariff_id_30', 'tariff_id_31', 'tariff_id_32', 'tariff_id_4', 'tariff_id_5', 'tariff_id_6', 'tariff_id_7', 'tariff_id_8', 'tariff_id_9', 'tariff_id_99', 'living_region_1.0', 'living_region_10.0', 'living_region_11.0', 'living_region_12.0', 'living_region_13.0', 'living_region_14.0', 'living_region_15.0', 'living_region_16.0', 'living_region_17.0', 'living_region_18.0', 'living_region_19.0', 'living_region_2.0', 'living_region_20.0', 'living_region_21.0', 'living_region_22.0', 'living_region_23.0', 'living_region_24.0', 'living_region_25.0', 'living_region_26.0', 'living_region_27.0', 'living_region_28.0', 'living_region_29.0', 'living_region_3.0', 'living_region_30.0', 'living_region_31.0', 'living_region_32.0', 'living_region_33.0', 'living_region_34.0', 'living_region_35.0', 'living_region_36.0', 'living_region_37.0', 'living_region_38.0', 'living_region_39.0', 'living_region_4.0', 'living_region_40.0', 'living_region_41.0', 'living_region_43.0', 'living_region_44.0', 'living_region_45.0', 'living_region_46.0', 'living_region_47.0', 'living_region_48.0', 'living_region_49.0', 'living_region_5.0', 'living_region_50.0', 'living_region_51.0', 'living_region_52.0', 'living_region_53.0', 'living_region_54.0', 'living_region_55.0', 'living_region_56.0', 'living_region_57.0', 'living_region_58.0', 'living_region_59.0', 'living_region_6.0', 'living_region_60.0', 'living_region_61.0', 'living_region_62.0', 'living_region_63.0', 'living_region_64.0', 'living_region_65.0', 'living_region_66.0', 'living_region_67.0', 'living_region_68.0', 'living_region_69.0', 'living_region_7.0', 'living_region_70.0', 'living_region_71.0', 'living_region_72.0', 'living_region_73.0', 'living_region_74.0', 'living_region_75.0', 'living_region_76.0', 'living_region_77.0', 'living_region_78.0', 'living_region_79.0', 'living_region_8.0', 'living_region_80.0', 'living_region_81.0', 'living_region_82.0', 'living_region_9.0', 'living_region_99', 'okrug_1.0', 'okrug_2.0', 'okrug_3.0', 'okrug_4.0', 'okrug_5.0', 'okrug_6.0', 'okrug_7.0', 'okrug_8.0', 'okrug_99', 'open_account_flg_0', 'open_account_flg_1']\n",
      "Исходные переменные:\n",
      " ['gender', 'age', 'marital_status', 'job_position', 'credit_sum', 'credit_month', 'score_shk', 'education', 'tariff_id', 'living_region', 'okrug', 'avregzarplata', 'monthly_income', 'credit_count', 'overdue_credit_count', 'open_account_flg'] \n",
      "\n",
      "Переменные после get_dummies:\n",
      " ['age', 'credit_sum', 'credit_month', 'score_shk', 'avregzarplata', 'monthly_income', 'credit_count', 'overdue_credit_count', 'gender_1', 'gender_2', 'marital_status_1.0', 'marital_status_2.0', 'marital_status_3.0', 'marital_status_4.0', 'marital_status_5.0', 'job_position_1', 'job_position_10', 'job_position_11', 'job_position_13', 'job_position_14', 'job_position_15', 'job_position_16', 'job_position_17', 'job_position_18', 'job_position_2', 'job_position_3', 'job_position_4', 'job_position_6', 'job_position_8', 'job_position_99', 'education_1.0', 'education_2.0', 'education_3.0', 'education_4.0', 'education_5.0', 'tariff_id_1', 'tariff_id_10', 'tariff_id_11', 'tariff_id_12', 'tariff_id_13', 'tariff_id_18', 'tariff_id_19', 'tariff_id_2', 'tariff_id_20', 'tariff_id_21', 'tariff_id_22', 'tariff_id_23', 'tariff_id_25', 'tariff_id_28', 'tariff_id_29', 'tariff_id_3', 'tariff_id_30', 'tariff_id_31', 'tariff_id_32', 'tariff_id_4', 'tariff_id_5', 'tariff_id_6', 'tariff_id_7', 'tariff_id_8', 'tariff_id_9', 'tariff_id_99', 'living_region_1.0', 'living_region_10.0', 'living_region_11.0', 'living_region_12.0', 'living_region_13.0', 'living_region_14.0', 'living_region_15.0', 'living_region_16.0', 'living_region_17.0', 'living_region_18.0', 'living_region_19.0', 'living_region_2.0', 'living_region_20.0', 'living_region_21.0', 'living_region_22.0', 'living_region_23.0', 'living_region_24.0', 'living_region_25.0', 'living_region_26.0', 'living_region_27.0', 'living_region_28.0', 'living_region_29.0', 'living_region_3.0', 'living_region_30.0', 'living_region_31.0', 'living_region_32.0', 'living_region_33.0', 'living_region_34.0', 'living_region_35.0', 'living_region_36.0', 'living_region_37.0', 'living_region_38.0', 'living_region_39.0', 'living_region_4.0', 'living_region_40.0', 'living_region_41.0', 'living_region_43.0', 'living_region_44.0', 'living_region_45.0', 'living_region_46.0', 'living_region_47.0', 'living_region_48.0', 'living_region_49.0', 'living_region_5.0', 'living_region_50.0', 'living_region_51.0', 'living_region_52.0', 'living_region_53.0', 'living_region_54.0', 'living_region_55.0', 'living_region_56.0', 'living_region_57.0', 'living_region_58.0', 'living_region_59.0', 'living_region_6.0', 'living_region_60.0', 'living_region_61.0', 'living_region_62.0', 'living_region_63.0', 'living_region_64.0', 'living_region_65.0', 'living_region_66.0', 'living_region_67.0', 'living_region_68.0', 'living_region_69.0', 'living_region_7.0', 'living_region_70.0', 'living_region_71.0', 'living_region_72.0', 'living_region_73.0', 'living_region_74.0', 'living_region_75.0', 'living_region_76.0', 'living_region_77.0', 'living_region_78.0', 'living_region_79.0', 'living_region_8.0', 'living_region_80.0', 'living_region_81.0', 'living_region_82.0', 'living_region_9.0', 'living_region_99', 'okrug_1.0', 'okrug_2.0', 'okrug_3.0', 'okrug_4.0', 'okrug_5.0', 'okrug_6.0', 'okrug_7.0', 'okrug_8.0', 'okrug_99', 'open_account_flg_0', 'open_account_flg_1']\n"
     ]
    }
   ],
   "source": [
    "print(\"Исходные переменные:\\n\", list(train.columns), \"\\n\")\n",
    "train_dummies = pd.get_dummies(train)\n",
    "print(\"Переменные после get_dummies:\\n\", list(train_dummies.columns))\n",
    "\n",
    "print(\"Исходные переменные:\\n\", list(test.columns), \"\\n\")\n",
    "test_dummies = pd.get_dummies(test)\n",
    "print(\"Переменные после get_dummies:\\n\", list(test_dummies.columns))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Построение стандартной модели случайного леса"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "y_train = train_dummies.loc[:, 'open_account_flg_1']\n",
    "y_test = test_dummies.loc[:, 'open_account_flg_1']\n",
    "X_train = train_dummies.loc[:, 'age':'okrug_99']\n",
    "X_test = test_dummies.loc[:, 'age':'okrug_99']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC на обучающей выборке: 1.000\n",
      "AUC на контрольной выборке: 0.743\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "forest=RandomForestClassifier(n_estimators=800, random_state=152, n_jobs=-1)\n",
    "forest.fit(X_train, y_train)\n",
    "from sklearn.metrics import roc_auc_score\n",
    "print(\"AUC на обучающей выборке: {:.3f}\".format(roc_auc_score(y_train, forest.predict_proba(X_train)[:, 1])))\n",
    "print(\"AUC на контрольной выборке: {:.3f}\".format(roc_auc_score(y_test, forest.predict_proba(X_test)[:, 1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.tree import _tree\n",
    "\n",
    "# Пишем функцию, которая вычисляет глубину терминальных \n",
    "# узлов в отдельном дереве\n",
    "def leaf_depths(tree, node_id = 0):\n",
    "\n",
    "    '''\n",
    "    tree.children_left и tree.children_right записывают идентификационные\n",
    "    номера левого и правого узлов-потомков для данного узла\n",
    "    '''\n",
    "\n",
    "    left_child = tree.children_left[node_id]\n",
    "    right_child = tree.children_right[node_id]\n",
    "\n",
    "    '''\n",
    "    Если данный узел является терминальным, \n",
    "    то оба дочерних узла будут иметь значение _tree.TREE_LEAF,\n",
    "    что позволяет нам проверить, является ли данный узел терминальным\n",
    "    '''\n",
    "\n",
    "    if left_child == _tree.TREE_LEAF:\n",
    "      \n",
    "       '''\n",
    "       Задать глубину терминальных узлов равной 0\n",
    "       '''\n",
    "      \n",
    "       depths = np.array([0])\n",
    "\n",
    "    else:\n",
    "     \n",
    "        '''\n",
    "        Получить значения глубины узлов-потомков\n",
    "        и увеличить их на 1\n",
    "        '''\n",
    "        \n",
    "        left_depths = leaf_depths(tree, left_child) + 1\n",
    "        right_depths = leaf_depths(tree, right_child) + 1\n",
    " \n",
    "        depths = np.append(left_depths, right_depths)\n",
    " \n",
    "    return depths\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Пишем функцию, которая вычисляет минимальное количество наблюдений \n",
    "# в терминальных узлах отдельного дерева\n",
    "def leaf_samples(tree, node_id = 0):\n",
    "    \n",
    "    left_child = tree.children_left[node_id]\n",
    "    right_child = tree.children_right[node_id]\n",
    "\n",
    "    if left_child == _tree.TREE_LEAF:\n",
    "        \n",
    "         samples = np.array([tree.n_node_samples[node_id]])\n",
    "\n",
    "    else:\n",
    "        \n",
    "        left_samples = leaf_samples(tree, left_child)\n",
    "        right_samples = leaf_samples(tree, right_child)\n",
    "\n",
    "        samples = np.append(left_samples, right_samples)\n",
    "\n",
    "    return samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Пишем функцию, которая строит гистограмму распределения \n",
    "# глубин терминальных узлов и гистограмму распределения \n",
    "# количества наблюдений в терминальных узлах по ансамблю\n",
    "def draw_ensemble(ensemble):\n",
    "\n",
    "    plt.figure(figsize=(8,8))\n",
    "    plt.subplot(211)\n",
    "\n",
    "    depths_all = np.array([], dtype=int)\n",
    "\n",
    "    for x in ensemble.estimators_:\n",
    "        tree = x.tree_\n",
    "        depths = leaf_depths(tree)\n",
    "        depths_all = np.append(depths_all, depths)\n",
    "        plt.hist(depths, histtype='step', color='#ddaaff', \n",
    "                 bins=range(min(depths), max(depths)+1))\n",
    "\n",
    "    plt.hist(depths_all, histtype='step', color='#9933ff', \n",
    "             bins=range(min(depths_all), max(depths_all)+1), \n",
    "             weights=np.ones(len(depths_all))/len(ensemble.estimators_), \n",
    "             linewidth=2)\n",
    "    plt.xlabel(\"Глубина терминальных узлов\")\n",
    "   \n",
    "    samples_all = np.array([], dtype=int)\n",
    "    \n",
    "    plt.subplot(212)\n",
    "    \n",
    "    for x in ensemble.estimators_:\n",
    "        tree = x.tree_\n",
    "        samples = leaf_samples(tree)\n",
    "        samples_all = np.append(samples_all, samples)\n",
    "        plt.hist(samples, histtype='step', color='#aaddff', \n",
    "                 bins=range(min(samples), max(samples)+1))\n",
    "    \n",
    "    plt.hist(samples_all, histtype='step', color='#3399ff', \n",
    "             bins=range(min(samples_all), max(samples_all)+1), \n",
    "             weights=np.ones(len(samples_all))/len(ensemble.estimators_), \n",
    "             linewidth=2)\n",
    "    plt.xlabel(\"Количество наблюдений в терминальных узлах\")\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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w3j2U8i3DJLGCcBksExHR6seAmGihQqtcCnhNbKFawQNyle0GojmhosNIGuFkwnPFZ4j9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\nF2vB0CRdJ2kjQO3KEuguhxFiTSWUduKwv88e+OqNbhSXjssyNwJNJVi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du3ezfPlyYmNj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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cc176c5278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_ensemble(forest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC на обучающей выборке: 0.922\n",
      "AUC на контрольной выборке: 0.761\n"
     ]
    }
   ],
   "source": [
    "forest2=RandomForestClassifier(n_estimators=800, max_depth=20, random_state=152, n_jobs=-1)\n",
    "forest2.fit(X_train, y_train)\n",
    "print(\"AUC на обучающей выборке: {:.3f}\".format(roc_auc_score(y_train, forest2.predict_proba(X_train)[:, 1])))\n",
    "print(\"AUC на контрольной выборке: {:.3f}\".format(roc_auc_score(y_test, forest2.predict_proba(X_test)[:, 1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC на обучающей выборке: 0.841\n",
      "AUC на контрольной выборке: 0.760\n"
     ]
    }
   ],
   "source": [
    "forest3=RandomForestClassifier(n_estimators=800, min_samples_leaf=10, random_state=152, n_jobs=-1)\n",
    "forest3.fit(X_train, y_train)\n",
    "print(\"AUC на обучающей выборке: {:.3f}\".format(roc_auc_score(y_train, forest3.predict_proba(X_train)[:, 1])))\n",
    "print(\"AUC на контрольной выборке: {:.3f}\".format(roc_auc_score(y_test, forest3.predict_proba(X_test)[:, 1])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Применение стандартной модели случайного леса к новым данным"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>client_id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>job_position</th>\n",
       "      <th>credit_sum</th>\n",
       "      <th>credit_month</th>\n",
       "      <th>score_shk</th>\n",
       "      <th>education</th>\n",
       "      <th>tariff_id</th>\n",
       "      <th>living_region</th>\n",
       "      <th>okrug</th>\n",
       "      <th>avregzarplata</th>\n",
       "      <th>monthly_income</th>\n",
       "      <th>credit_count</th>\n",
       "      <th>overdue_credit_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>170747</td>\n",
       "      <td>2</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14</td>\n",
       "      <td>16558</td>\n",
       "      <td>10</td>\n",
       "      <td>0,370409</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>23.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>25850.0</td>\n",
       "      <td>34000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>170748</td>\n",
       "      <td>2</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
       "      <td>7028,72</td>\n",
       "      <td>6</td>\n",
       "      <td>0,377281</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>66880.0</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>170749</td>\n",
       "      <td>1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>14</td>\n",
       "      <td>13019</td>\n",
       "      <td>10</td>\n",
       "      <td>0,538515</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>64.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23430.0</td>\n",
       "      <td>25000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>170750</td>\n",
       "      <td>2</td>\n",
       "      <td>41.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8</td>\n",
       "      <td>9379</td>\n",
       "      <td>10</td>\n",
       "      <td>0,48252</td>\n",
       "      <td>4.0</td>\n",
       "      <td>28</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23650.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>170751</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14</td>\n",
       "      <td>13990</td>\n",
       "      <td>6</td>\n",
       "      <td>0,485914</td>\n",
       "      <td>2.0</td>\n",
       "      <td>28</td>\n",
       "      <td>77.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>26620.0</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   client_id  gender   age  marital_status  job_position credit_sum  \\\n",
       "0     170747       2  48.0             1.0            14      16558   \n",
       "1     170748       2  29.0             3.0            14    7028,72   \n",
       "2     170749       1  20.0             2.0            14      13019   \n",
       "3     170750       2  41.0             4.0             8       9379   \n",
       "4     170751       2   NaN             4.0            14      13990   \n",
       "\n",
       "   credit_month score_shk  education  tariff_id  living_region  okrug  \\\n",
       "0            10  0,370409        4.0          2           23.0    8.0   \n",
       "1             6  0,377281        4.0          2           30.0    7.0   \n",
       "2            10  0,538515        2.0          2           64.0    2.0   \n",
       "3            10   0,48252        4.0         28            8.0    8.0   \n",
       "4             6  0,485914        2.0         28           77.0    6.0   \n",
       "\n",
       "   avregzarplata  monthly_income  credit_count  overdue_credit_count  \n",
       "0        25850.0         34000.0           2.0                   0.0  \n",
       "1        66880.0         19000.0           3.0                   0.0  \n",
       "2        23430.0         25000.0           1.0                   0.0  \n",
       "3        23650.0         30000.0           0.0                   0.0  \n",
       "4        26620.0         20000.0           2.0                   0.0  "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newdata = pd.read_csv(\"C:/Trees/Credit_new.csv\", encoding='cp1251', sep=';')\n",
    "newdata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "client_id=newdata['client_id']\n",
    "del newdata['client_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 91940 entries, 0 to 91939\n",
      "Data columns (total 15 columns):\n",
      "gender                  91940 non-null int64\n",
      "age                     91938 non-null float64\n",
      "marital_status          91938 non-null float64\n",
      "job_position            91940 non-null int64\n",
      "credit_sum              91939 non-null object\n",
      "credit_month            91940 non-null int64\n",
      "score_shk               91939 non-null object\n",
      "education               91938 non-null float64\n",
      "tariff_id               91940 non-null int64\n",
      "living_region           91834 non-null float64\n",
      "okrug                   91834 non-null float64\n",
      "avregzarplata           91834 non-null float64\n",
      "monthly_income          91939 non-null float64\n",
      "credit_count            87237 non-null float64\n",
      "overdue_credit_count    87237 non-null float64\n",
      "dtypes: float64(9), int64(4), object(2)\n",
      "memory usage: 10.5+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(newdata.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in ['gender', 'marital_status', 'job_position', 'education', \n",
    "          'tariff_id', 'living_region', 'okrug']:\n",
    "    if i in newdata.columns:\n",
    "        newdata[i]=newdata[i].astype('str')\n",
    "\n",
    "newdata['credit_sum'] = newdata['credit_sum'].str.replace(',', '.')\n",
    "newdata['score_shk'] = newdata['score_shk'].str.replace(',', '.')\n",
    "newdata['credit_sum'] = newdata['credit_sum'].astype('float')\n",
    "newdata['score_shk'] = newdata['score_shk'].astype('float')\n",
    "\n",
    "newdata.at[newdata['job_position'] == '5', 'job_position'] = '99'\n",
    "newdata.at[newdata['job_position'] == '7', 'job_position'] = '99'\n",
    "newdata.at[newdata['job_position'] == '9', 'job_position'] = '99'\n",
    "newdata.at[newdata['job_position'] == '12', 'job_position'] = '99'\n",
    "\n",
    "newdata.at[newdata['tariff_id'] == '14', 'tariff_id'] = '99'\n",
    "newdata.at[newdata['tariff_id'] == '15', 'tariff_id'] = '99'\n",
    "newdata.at[newdata['tariff_id'] == '16', 'tariff_id'] = '99'\n",
    "newdata.at[newdata['tariff_id'] == '17', 'tariff_id'] = '99'\n",
    "newdata.at[newdata['tariff_id'] == '24', 'tariff_id'] = '99'\n",
    "newdata.at[newdata['tariff_id'] == '26', 'tariff_id'] = '99'\n",
    "newdata.at[newdata['tariff_id'] == '27', 'tariff_id'] = '99'\n",
    "newdata.at[newdata['tariff_id'] == '33', 'tariff_id'] = '99'\n",
    "\n",
    "for i in ['age', 'credit_sum', 'score_shk', 'monthly_income']:\n",
    "    if i in newdata.columns:\n",
    "        newdata[i].fillna(newdata[i].median(), inplace=True)\n",
    "\n",
    "for i in ['avregzarplata', 'credit_count', 'overdue_credit_count']:\n",
    "    if i in newdata.columns:\n",
    "        newdata[i].fillna(-1, inplace=True)\n",
    "\n",
    "newdata.at[newdata['marital_status'] == 'nan', 'marital_status'] = '3.0'\n",
    "newdata.at[newdata['education'] == 'nan', 'education'] = '4.0'\n",
    "newdata.at[newdata['living_region'] == 'nan', 'living_region'] = '99'\n",
    "newdata.at[newdata['okrug'] == 'nan', 'okrug'] = '99'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 91940 entries, 0 to 91939\n",
      "Data columns (total 15 columns):\n",
      "gender                  91940 non-null object\n",
      "age                     91940 non-null float64\n",
      "marital_status          91940 non-null object\n",
      "job_position            91940 non-null object\n",
      "credit_sum              91940 non-null float64\n",
      "credit_month            91940 non-null int64\n",
      "score_shk               91940 non-null float64\n",
      "education               91940 non-null object\n",
      "tariff_id               91940 non-null object\n",
      "living_region           91940 non-null object\n",
      "okrug                   91940 non-null object\n",
      "avregzarplata           91940 non-null float64\n",
      "monthly_income          91940 non-null float64\n",
      "credit_count            91940 non-null float64\n",
      "overdue_credit_count    91940 non-null float64\n",
      "dtypes: float64(7), int64(1), object(7)\n",
      "memory usage: 10.5+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(newdata.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Исходные переменные:\n",
      " ['gender', 'age', 'marital_status', 'job_position', 'credit_sum', 'credit_month', 'score_shk', 'education', 'tariff_id', 'living_region', 'okrug', 'avregzarplata', 'monthly_income', 'credit_count', 'overdue_credit_count'] \n",
      "\n",
      "Переменные после get_dummies:\n",
      " ['age', 'credit_sum', 'credit_month', 'score_shk', 'avregzarplata', 'monthly_income', 'credit_count', 'overdue_credit_count', 'gender_1', 'gender_2', 'marital_status_1.0', 'marital_status_2.0', 'marital_status_3.0', 'marital_status_4.0', 'marital_status_5.0', 'job_position_1', 'job_position_10', 'job_position_11', 'job_position_13', 'job_position_14', 'job_position_15', 'job_position_16', 'job_position_17', 'job_position_18', 'job_position_2', 'job_position_3', 'job_position_4', 'job_position_6', 'job_position_8', 'job_position_99', 'education_1.0', 'education_2.0', 'education_3.0', 'education_4.0', 'education_5.0', 'tariff_id_1', 'tariff_id_10', 'tariff_id_11', 'tariff_id_12', 'tariff_id_13', 'tariff_id_18', 'tariff_id_19', 'tariff_id_2', 'tariff_id_20', 'tariff_id_21', 'tariff_id_22', 'tariff_id_23', 'tariff_id_25', 'tariff_id_28', 'tariff_id_29', 'tariff_id_3', 'tariff_id_30', 'tariff_id_31', 'tariff_id_32', 'tariff_id_4', 'tariff_id_5', 'tariff_id_6', 'tariff_id_7', 'tariff_id_8', 'tariff_id_9', 'tariff_id_99', 'living_region_1.0', 'living_region_10.0', 'living_region_11.0', 'living_region_12.0', 'living_region_13.0', 'living_region_14.0', 'living_region_15.0', 'living_region_16.0', 'living_region_17.0', 'living_region_18.0', 'living_region_19.0', 'living_region_2.0', 'living_region_20.0', 'living_region_21.0', 'living_region_22.0', 'living_region_23.0', 'living_region_24.0', 'living_region_25.0', 'living_region_26.0', 'living_region_27.0', 'living_region_28.0', 'living_region_29.0', 'living_region_3.0', 'living_region_30.0', 'living_region_31.0', 'living_region_32.0', 'living_region_33.0', 'living_region_34.0', 'living_region_35.0', 'living_region_36.0', 'living_region_37.0', 'living_region_38.0', 'living_region_39.0', 'living_region_4.0', 'living_region_40.0', 'living_region_41.0', 'living_region_43.0', 'living_region_44.0', 'living_region_45.0', 'living_region_46.0', 'living_region_47.0', 'living_region_48.0', 'living_region_49.0', 'living_region_5.0', 'living_region_50.0', 'living_region_51.0', 'living_region_52.0', 'living_region_53.0', 'living_region_54.0', 'living_region_55.0', 'living_region_56.0', 'living_region_57.0', 'living_region_58.0', 'living_region_59.0', 'living_region_6.0', 'living_region_60.0', 'living_region_61.0', 'living_region_62.0', 'living_region_63.0', 'living_region_64.0', 'living_region_65.0', 'living_region_66.0', 'living_region_67.0', 'living_region_68.0', 'living_region_69.0', 'living_region_7.0', 'living_region_70.0', 'living_region_71.0', 'living_region_72.0', 'living_region_73.0', 'living_region_74.0', 'living_region_75.0', 'living_region_76.0', 'living_region_77.0', 'living_region_78.0', 'living_region_79.0', 'living_region_8.0', 'living_region_80.0', 'living_region_81.0', 'living_region_82.0', 'living_region_9.0', 'living_region_99', 'okrug_1.0', 'okrug_2.0', 'okrug_3.0', 'okrug_4.0', 'okrug_5.0', 'okrug_6.0', 'okrug_7.0', 'okrug_8.0', 'okrug_99']\n"
     ]
    }
   ],
   "source": [
    "print(\"Исходные переменные:\\n\", list(newdata.columns), \"\\n\")\n",
    "newdata_dummies = pd.get_dummies(newdata)\n",
    "print(\"Переменные после get_dummies:\\n\", list(newdata_dummies.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.87425165,  0.12574835],\n",
       "       [ 0.67140306,  0.32859694],\n",
       "       [ 0.80812115,  0.19187885],\n",
       "       ..., \n",
       "       [ 0.66680124,  0.33319876],\n",
       "       [ 0.64507592,  0.35492408],\n",
       "       [ 0.91713663,  0.08286337]])"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prob = forest3.predict_proba(newdata_dummies)\n",
    "prob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Prob0</th>\n",
       "      <th>Prob1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.874252</td>\n",
       "      <td>0.125748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.671403</td>\n",
       "      <td>0.328597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.808121</td>\n",
       "      <td>0.191879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.745555</td>\n",
       "      <td>0.254445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.873426</td>\n",
       "      <td>0.126574</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Prob0     Prob1\n",
       "0  0.874252  0.125748\n",
       "1  0.671403  0.328597\n",
       "2  0.808121  0.191879\n",
       "3  0.745555  0.254445\n",
       "4  0.873426  0.126574"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "probabilities=pd.DataFrame(prob, index=newdata.index, columns=['Prob0', 'Prob1'])\n",
    "probabilities.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>client_id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>marital_status</th>\n",
       "      <th>job_position</th>\n",
       "      <th>credit_sum</th>\n",
       "      <th>credit_month</th>\n",
       "      <th>score_shk</th>\n",
       "      <th>education</th>\n",
       "      <th>tariff_id</th>\n",
       "      <th>living_region</th>\n",
       "      <th>okrug</th>\n",
       "      <th>avregzarplata</th>\n",
       "      <th>monthly_income</th>\n",
       "      <th>credit_count</th>\n",
       "      <th>overdue_credit_count</th>\n",
       "      <th>Prob0</th>\n",
       "      <th>Prob1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>170747</td>\n",
       "      <td>2</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14</td>\n",
       "      <td>16558.00</td>\n",
       "      <td>10</td>\n",
       "      <td>0.370409</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>23.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>25850.0</td>\n",
       "      <td>34000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.874252</td>\n",
       "      <td>0.125748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>170748</td>\n",
       "      <td>2</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14</td>\n",
       "      <td>7028.72</td>\n",
       "      <td>6</td>\n",
       "      <td>0.377281</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>66880.0</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.671403</td>\n",
       "      <td>0.328597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>170749</td>\n",
       "      <td>1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>14</td>\n",
       "      <td>13019.00</td>\n",
       "      <td>10</td>\n",
       "      <td>0.538515</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>64.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23430.0</td>\n",
       "      <td>25000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.808121</td>\n",
       "      <td>0.191879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>170750</td>\n",
       "      <td>2</td>\n",
       "      <td>41.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8</td>\n",
       "      <td>9379.00</td>\n",
       "      <td>10</td>\n",
       "      <td>0.482520</td>\n",
       "      <td>4.0</td>\n",
       "      <td>28</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23650.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.745555</td>\n",
       "      <td>0.254445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>170751</td>\n",
       "      <td>2</td>\n",
       "      <td>34.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14</td>\n",
       "      <td>13990.00</td>\n",
       "      <td>6</td>\n",
       "      <td>0.485914</td>\n",
       "      <td>2.0</td>\n",
       "      <td>28</td>\n",
       "      <td>77.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>26620.0</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.873426</td>\n",
       "      <td>0.126574</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   client_id gender   age marital_status job_position  credit_sum  \\\n",
       "0     170747      2  48.0            1.0           14    16558.00   \n",
       "1     170748      2  29.0            3.0           14     7028.72   \n",
       "2     170749      1  20.0            2.0           14    13019.00   \n",
       "3     170750      2  41.0            4.0            8     9379.00   \n",
       "4     170751      2  34.0            4.0           14    13990.00   \n",
       "\n",
       "   credit_month  score_shk education tariff_id living_region okrug  \\\n",
       "0            10   0.370409       4.0         2          23.0   8.0   \n",
       "1             6   0.377281       4.0         2          30.0   7.0   \n",
       "2            10   0.538515       2.0         2          64.0   2.0   \n",
       "3            10   0.482520       4.0        28           8.0   8.0   \n",
       "4             6   0.485914       2.0        28          77.0   6.0   \n",
       "\n",
       "   avregzarplata  monthly_income  credit_count  overdue_credit_count  \\\n",
       "0        25850.0         34000.0           2.0                   0.0   \n",
       "1        66880.0         19000.0           3.0                   0.0   \n",
       "2        23430.0         25000.0           1.0                   0.0   \n",
       "3        23650.0         30000.0           0.0                   0.0   \n",
       "4        26620.0         20000.0           2.0                   0.0   \n",
       "\n",
       "      Prob0     Prob1  \n",
       "0  0.874252  0.125748  \n",
       "1  0.671403  0.328597  \n",
       "2  0.808121  0.191879  \n",
       "3  0.745555  0.254445  \n",
       "4  0.873426  0.126574  "
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result=pd.concat([client_id, newdata, probabilities], axis=1)\n",
    "result.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "result.to_csv('C:\\\\Trees\\\\Credit_result.csv', sep=';')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pandas import ExcelWriter\n",
    "writer = ExcelWriter('C:\\\\Trees\\\\Credit_result.xlsx')\n",
    "result.to_excel(writer,'Sheet1')\n",
    "writer.save()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Подготовка данных для моделирования в H2O"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking whether there is an H2O instance running at http://localhost:54321..... not found.\n",
      "Attempting to start a local H2O server...\n",
      "; Java HotSpot(TM) 64-Bit Server VM (build 25.121-b13, mixed mode)\n",
      "  Starting server from C:\\Anaconda3\\lib\\site-packages\\h2o\\backend\\bin\\h2o.jar\n",
      "  Ice root: C:\\Users\\Gewissta\\AppData\\Local\\Temp\\tmpz4unp_0y\n",
      "  JVM stdout: C:\\Users\\Gewissta\\AppData\\Local\\Temp\\tmpz4unp_0y\\h2o_Gewissta_started_from_python.out\n",
      "  JVM stderr: C:\\Users\\Gewissta\\AppData\\Local\\Temp\\tmpz4unp_0y\\h2o_Gewissta_started_from_python.err\n",
      "  Server is running at http://127.0.0.1:54321\n",
      "Connecting to H2O server at http://127.0.0.1:54321... successful.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td>H2O cluster uptime:</td>\n",
       "<td>05 secs</td></tr>\n",
       "<tr><td>H2O cluster version:</td>\n",
       "<td>3.10.4.8</td></tr>\n",
       "<tr><td>H2O cluster version age:</td>\n",
       "<td>1 month and 21 days </td></tr>\n",
       "<tr><td>H2O cluster name:</td>\n",
       "<td>H2O_from_python_Gewissta_cn3gmg</td></tr>\n",
       "<tr><td>H2O cluster total nodes:</td>\n",
       "<td>1</td></tr>\n",
       "<tr><td>H2O cluster free memory:</td>\n",
       "<td>7.111 Gb</td></tr>\n",
       "<tr><td>H2O cluster total cores:</td>\n",
       "<td>4</td></tr>\n",
       "<tr><td>H2O cluster allowed cores:</td>\n",
       "<td>4</td></tr>\n",
       "<tr><td>H2O cluster status:</td>\n",
       "<td>accepting new members, healthy</td></tr>\n",
       "<tr><td>H2O connection url:</td>\n",
       "<td>http://127.0.0.1:54321</td></tr>\n",
       "<tr><td>H2O connection proxy:</td>\n",
       "<td>None</td></tr>\n",
       "<tr><td>H2O internal security:</td>\n",
       "<td>False</td></tr>\n",
       "<tr><td>Python version:</td>\n",
       "<td>3.5.2 final</td></tr></table></div>"
      ],
      "text/plain": [
       "--------------------------  -------------------------------\n",
       "H2O cluster uptime:         05 secs\n",
       "H2O cluster version:        3.10.4.8\n",
       "H2O cluster version age:    1 month and 21 days\n",
       "H2O cluster name:           H2O_from_python_Gewissta_cn3gmg\n",
       "H2O cluster total nodes:    1\n",
       "H2O cluster free memory:    7.111 Gb\n",
       "H2O cluster total cores:    4\n",
       "H2O cluster allowed cores:  4\n",
       "H2O cluster status:         accepting new members, healthy\n",
       "H2O connection url:         http://127.0.0.1:54321\n",
       "H2O connection proxy:\n",
       "H2O internal security:      False\n",
       "Python version:             3.5.2 final\n",
       "--------------------------  -------------------------------"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Перед импортом модулей h2o и os убедитесь, что модуль h2o установлен (в противном\n",
    "# случае запустите в Anaconda Prompt строку pip install h2o)\n",
    "import h2o\n",
    "import os\n",
    "h2o.init(nthreads = -1, max_mem_size = 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parse progress: |█████████████████████████████████████████████████████████| 100%\n",
      "Parse progress: |█████████████████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "training = h2o.H2OFrame(train)\n",
    "validation = h2o.H2OFrame(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rows:119522\n",
      "Cols:16\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>       </th><th>gender             </th><th>age               </th><th>marital_status    </th><th>job_position      </th><th>credit_sum        </th><th>credit_month      </th><th>score_shk          </th><th>education         </th><th>tariff_id         </th><th>living_region     </th><th>okrug             </th><th>avregzarplata     </th><th>monthly_income    </th><th>credit_count      </th><th>overdue_credit_count  </th><th>open_account_flg  </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td>type   </td><td>int                </td><td>int               </td><td>int               </td><td>int               </td><td>real              </td><td>int               </td><td>real               </td><td>int               </td><td>int               </td><td>int               </td><td>int               </td><td>int               </td><td>int               </td><td>int               </td><td>int                   </td><td>int               </td></tr>\n",
       "<tr><td>mins   </td><td>1.0                </td><td>18.0              </td><td>1.0               </td><td>1.0               </td><td>2736.0            </td><td>3.0               </td><td>0.0                </td><td>1.0               </td><td>1.0               </td><td>1.0               </td><td>1.0               </td><td>-1.0              </td><td>5000.0            </td><td>-1.0              </td><td>-1.0                  </td><td>0.0               </td></tr>\n",
       "<tr><td>mean   </td><td>1.48038018105454   </td><td>36.47966901490917 </td><td>3.1977292883318396</td><td>13.176369203995893</td><td>26084.894492980507</td><td>10.976665383778691</td><td>0.46972772229380194</td><td>3.2007663861046445</td><td>14.161593681497939</td><td>43.052425494887984</td><td>4.920868124696686 </td><td>32914.489391074465</td><td>40108.71866267324 </td><td>1.937241679356102 </td><td>-0.011094191864259289 </td><td>0.175858837703519 </td></tr>\n",
       "<tr><td>maxs   </td><td>2.0                </td><td>71.0              </td><td>5.0               </td><td>99.0              </td><td>200000.0          </td><td>36.0              </td><td>1.128291           </td><td>5.0               </td><td>99.0              </td><td>99.0              </td><td>99.0              </td><td>66880.0           </td><td>900000.0          </td><td>21.0              </td><td>3.0                   </td><td>1.0               </td></tr>\n",
       "<tr><td>sigma  </td><td>0.49961700448094565</td><td>10.552338060975382</td><td>0.7391875522296649</td><td>3.2791497110712022</td><td>16229.781427175598</td><td>3.517199978903236 </td><td>0.12416084700379564</td><td>1.0644762772006513</td><td>11.6086704696823  </td><td>22.30658574774648 </td><td>3.9264981210288967</td><td>12628.327179426848</td><td>25056.337758251655</td><td>1.8684854669182145</td><td>0.31294568174117793   </td><td>0.380701614806553 </td></tr>\n",
       "<tr><td>zeros  </td><td>0                  </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>1                  </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>18134             </td><td>107935                </td><td>98503             </td></tr>\n",
       "<tr><td>missing</td><td>0                  </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                  </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                     </td><td>0                 </td></tr>\n",
       "<tr><td>0      </td><td>2.0                </td><td>28.0              </td><td>4.0               </td><td>14.0              </td><td>33579.0           </td><td>10.0              </td><td>0.43135999999999997</td><td>4.0               </td><td>20.0              </td><td>2.0               </td><td>1.0               </td><td>34540.0           </td><td>36000.0           </td><td>2.0               </td><td>0.0                   </td><td>0.0               </td></tr>\n",
       "<tr><td>1      </td><td>2.0                </td><td>38.0              </td><td>4.0               </td><td>14.0              </td><td>23511.0           </td><td>10.0              </td><td>0.35847199999999996</td><td>2.0               </td><td>19.0              </td><td>68.0              </td><td>4.0               </td><td>22000.0           </td><td>45000.0           </td><td>2.0               </td><td>0.0                   </td><td>0.0               </td></tr>\n",
       "<tr><td>2      </td><td>1.0                </td><td>25.0              </td><td>3.0               </td><td>14.0              </td><td>39990.0           </td><td>24.0              </td><td>0.613475           </td><td>2.0               </td><td>25.0              </td><td>60.0              </td><td>8.0               </td><td>23320.0           </td><td>50000.0           </td><td>6.0               </td><td>0.0                   </td><td>0.0               </td></tr>\n",
       "<tr><td>3      </td><td>1.0                </td><td>65.0              </td><td>4.0               </td><td>15.0              </td><td>3490.0            </td><td>6.0               </td><td>0.371355           </td><td>2.0               </td><td>18.0              </td><td>59.0              </td><td>5.0               </td><td>32010.0           </td><td>35000.0           </td><td>4.0               </td><td>0.0                   </td><td>0.0               </td></tr>\n",
       "<tr><td>4      </td><td>2.0                </td><td>49.0              </td><td>3.0               </td><td>2.0               </td><td>36358.0           </td><td>10.0              </td><td>0.645187           </td><td>4.0               </td><td>28.0              </td><td>77.0              </td><td>6.0               </td><td>26620.0           </td><td>50000.0           </td><td>2.0               </td><td>0.0                   </td><td>0.0               </td></tr>\n",
       "<tr><td>5      </td><td>1.0                </td><td>39.0              </td><td>4.0               </td><td>14.0              </td><td>13209.0           </td><td>10.0              </td><td>0.45511999999999997</td><td>4.0               </td><td>2.0               </td><td>55.0              </td><td>1.0               </td><td>53460.0           </td><td>60000.0           </td><td>1.0               </td><td>0.0                   </td><td>0.0               </td></tr>\n",
       "<tr><td>6      </td><td>2.0                </td><td>30.0              </td><td>4.0               </td><td>14.0              </td><td>15192.050000000001</td><td>12.0              </td><td>0.451993           </td><td>4.0               </td><td>2.0               </td><td>57.0              </td><td>2.0               </td><td>27060.0           </td><td>25000.0           </td><td>1.0               </td><td>0.0                   </td><td>0.0               </td></tr>\n",
       "<tr><td>7      </td><td>1.0                </td><td>44.0              </td><td>5.0               </td><td>14.0              </td><td>27894.0           </td><td>10.0              </td><td>0.493069           </td><td>4.0               </td><td>19.0              </td><td>51.0              </td><td>3.0               </td><td>32450.0           </td><td>42600.0           </td><td>0.0               </td><td>0.0                   </td><td>1.0               </td></tr>\n",
       "<tr><td>8      </td><td>1.0                </td><td>33.0              </td><td>3.0               </td><td>14.0              </td><td>16116.470000000001</td><td>10.0              </td><td>0.479242           </td><td>4.0               </td><td>2.0               </td><td>20.0              </td><td>5.0               </td><td>17490.0           </td><td>20000.0           </td><td>4.0               </td><td>0.0                   </td><td>1.0               </td></tr>\n",
       "<tr><td>9      </td><td>1.0                </td><td>30.0              </td><td>4.0               </td><td>14.0              </td><td>3712.77           </td><td>6.0               </td><td>0.36771899999999996</td><td>4.0               </td><td>29.0              </td><td>33.0              </td><td>2.0               </td><td>26840.0           </td><td>20000.0           </td><td>3.0               </td><td>0.0                   </td><td>0.0               </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "training.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "training['gender'] = training['gender'].asfactor()\n",
    "training['marital_status'] = training['marital_status'].asfactor()\n",
    "training['job_position'] = training['job_position'].asfactor()\n",
    "training['education'] = training['education'].asfactor()\n",
    "training['tariff_id'] = training['tariff_id'].asfactor()\n",
    "training['living_region'] = training['living_region'].asfactor()\n",
    "training['okrug'] = training['okrug'].asfactor()\n",
    "training['open_account_flg'] = training['open_account_flg'].asfactor()\n",
    "\n",
    "validation['gender'] = validation['gender'].asfactor()\n",
    "validation['marital_status'] = validation['marital_status'].asfactor()\n",
    "validation['job_position'] = validation['job_position'].asfactor()\n",
    "validation['education'] = validation['education'].asfactor()\n",
    "validation['tariff_id'] = validation['tariff_id'].asfactor()\n",
    "validation['living_region'] = validation['living_region'].asfactor()\n",
    "validation['okrug'] = validation['okrug'].asfactor()\n",
    "validation['open_account_flg'] = validation['open_account_flg'].asfactor()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rows:119522\n",
      "Cols:16\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>       </th><th>gender  </th><th>age               </th><th>marital_status  </th><th>job_position  </th><th>credit_sum        </th><th>credit_month      </th><th>score_shk          </th><th>education  </th><th>tariff_id  </th><th>living_region  </th><th>okrug  </th><th>avregzarplata     </th><th>monthly_income    </th><th>credit_count      </th><th>overdue_credit_count  </th><th>open_account_flg  </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td>type   </td><td>enum    </td><td>int               </td><td>enum            </td><td>enum          </td><td>real              </td><td>int               </td><td>real               </td><td>enum       </td><td>enum       </td><td>enum           </td><td>enum   </td><td>int               </td><td>int               </td><td>int               </td><td>int                   </td><td>enum              </td></tr>\n",
       "<tr><td>mins   </td><td>        </td><td>18.0              </td><td>                </td><td>              </td><td>2736.0            </td><td>3.0               </td><td>0.0                </td><td>           </td><td>           </td><td>               </td><td>       </td><td>-1.0              </td><td>5000.0            </td><td>-1.0              </td><td>-1.0                  </td><td>                  </td></tr>\n",
       "<tr><td>mean   </td><td>        </td><td>36.47966901490917 </td><td>                </td><td>              </td><td>26084.894492980507</td><td>10.976665383778691</td><td>0.46972772229380194</td><td>           </td><td>           </td><td>               </td><td>       </td><td>32914.489391074465</td><td>40108.71866267324 </td><td>1.937241679356102 </td><td>-0.011094191864259289 </td><td>                  </td></tr>\n",
       "<tr><td>maxs   </td><td>        </td><td>71.0              </td><td>                </td><td>              </td><td>200000.0          </td><td>36.0              </td><td>1.128291           </td><td>           </td><td>           </td><td>               </td><td>       </td><td>66880.0           </td><td>900000.0          </td><td>21.0              </td><td>3.0                   </td><td>                  </td></tr>\n",
       "<tr><td>sigma  </td><td>        </td><td>10.552338060975382</td><td>                </td><td>              </td><td>16229.781427175598</td><td>3.517199978903236 </td><td>0.12416084700379564</td><td>           </td><td>           </td><td>               </td><td>       </td><td>12628.327179426848</td><td>25056.337758251655</td><td>1.8684854669182145</td><td>0.31294568174117793   </td><td>                  </td></tr>\n",
       "<tr><td>zeros  </td><td>        </td><td>0                 </td><td>                </td><td>              </td><td>0                 </td><td>0                 </td><td>1                  </td><td>           </td><td>           </td><td>               </td><td>       </td><td>0                 </td><td>0                 </td><td>18134             </td><td>107935                </td><td>                  </td></tr>\n",
       "<tr><td>missing</td><td>0       </td><td>0                 </td><td>0               </td><td>0             </td><td>0                 </td><td>0                 </td><td>0                  </td><td>0          </td><td>0          </td><td>0              </td><td>0      </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                     </td><td>0                 </td></tr>\n",
       "<tr><td>0      </td><td>2       </td><td>28.0              </td><td>4               </td><td>14            </td><td>33579.0           </td><td>10.0              </td><td>0.43135999999999997</td><td>4          </td><td>20         </td><td>2              </td><td>1      </td><td>34540.0           </td><td>36000.0           </td><td>2.0               </td><td>0.0                   </td><td>0                 </td></tr>\n",
       "<tr><td>1      </td><td>2       </td><td>38.0              </td><td>4               </td><td>14            </td><td>23511.0           </td><td>10.0              </td><td>0.35847199999999996</td><td>2          </td><td>19         </td><td>68             </td><td>4      </td><td>22000.0           </td><td>45000.0           </td><td>2.0               </td><td>0.0                   </td><td>0                 </td></tr>\n",
       "<tr><td>2      </td><td>1       </td><td>25.0              </td><td>3               </td><td>14            </td><td>39990.0           </td><td>24.0              </td><td>0.613475           </td><td>2          </td><td>25         </td><td>60             </td><td>8      </td><td>23320.0           </td><td>50000.0           </td><td>6.0               </td><td>0.0                   </td><td>0                 </td></tr>\n",
       "<tr><td>3      </td><td>1       </td><td>65.0              </td><td>4               </td><td>15            </td><td>3490.0            </td><td>6.0               </td><td>0.371355           </td><td>2          </td><td>18         </td><td>59             </td><td>5      </td><td>32010.0           </td><td>35000.0           </td><td>4.0               </td><td>0.0                   </td><td>0                 </td></tr>\n",
       "<tr><td>4      </td><td>2       </td><td>49.0              </td><td>3               </td><td>2             </td><td>36358.0           </td><td>10.0              </td><td>0.645187           </td><td>4          </td><td>28         </td><td>77             </td><td>6      </td><td>26620.0           </td><td>50000.0           </td><td>2.0               </td><td>0.0                   </td><td>0                 </td></tr>\n",
       "<tr><td>5      </td><td>1       </td><td>39.0              </td><td>4               </td><td>14            </td><td>13209.0           </td><td>10.0              </td><td>0.45511999999999997</td><td>4          </td><td>2          </td><td>55             </td><td>1      </td><td>53460.0           </td><td>60000.0           </td><td>1.0               </td><td>0.0                   </td><td>0                 </td></tr>\n",
       "<tr><td>6      </td><td>2       </td><td>30.0              </td><td>4               </td><td>14            </td><td>15192.050000000001</td><td>12.0              </td><td>0.451993           </td><td>4          </td><td>2          </td><td>57             </td><td>2      </td><td>27060.0           </td><td>25000.0           </td><td>1.0               </td><td>0.0                   </td><td>0                 </td></tr>\n",
       "<tr><td>7      </td><td>1       </td><td>44.0              </td><td>5               </td><td>14            </td><td>27894.0           </td><td>10.0              </td><td>0.493069           </td><td>4          </td><td>19         </td><td>51             </td><td>3      </td><td>32450.0           </td><td>42600.0           </td><td>0.0               </td><td>0.0                   </td><td>1                 </td></tr>\n",
       "<tr><td>8      </td><td>1       </td><td>33.0              </td><td>3               </td><td>14            </td><td>16116.470000000001</td><td>10.0              </td><td>0.479242           </td><td>4          </td><td>2          </td><td>20             </td><td>5      </td><td>17490.0           </td><td>20000.0           </td><td>4.0               </td><td>0.0                   </td><td>1                 </td></tr>\n",
       "<tr><td>9      </td><td>1       </td><td>30.0              </td><td>4               </td><td>14            </td><td>3712.77           </td><td>6.0               </td><td>0.36771899999999996</td><td>4          </td><td>29         </td><td>33             </td><td>2      </td><td>26840.0           </td><td>20000.0           </td><td>3.0               </td><td>0.0                   </td><td>0                 </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "training.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X = ['gender', 'age', 'marital_status', 'job_position', 'credit_sum', \n",
    "     'credit_month', 'score_shk', 'education', 'tariff_id', 'living_region', \n",
    "     'okrug', 'avregzarplata', 'monthly_income', 'credit_count',\n",
    "     'overdue_credit_count']\n",
    "y = 'open_account_flg'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Построение модели случайного леса с помощью класса H2ORandomForestEstimator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from h2o.estimators import H2ORandomForestEstimator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rf1 = H2ORandomForestEstimator(model_id='RF_credit', ntrees=800, max_depth=14, score_tree_interval=100, seed=1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "drf Model Build progress: |███████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "rf1.train(X, y, training_frame=training, validation_frame=validation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Details\n",
      "=============\n",
      "H2ORandomForestEstimator :  Distributed Random Forest\n",
      "Model Key:  RF_credit\n",
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on train data. **\n",
      "\n",
      "MSE: 0.12543831753065773\n",
      "RMSE: 0.35417272273660166\n",
      "LogLoss: 0.4007397887502991\n",
      "Mean Per-Class Error: 0.3037165105624732\n",
      "AUC: 0.7605262775277374\n",
      "Gini: 0.5210525550554748\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21448232967695893: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>74346.0</td>\n",
       "<td>24157.0</td>\n",
       "<td>0.2452</td>\n",
       "<td> (24157.0/98503.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>7958.0</td>\n",
       "<td>13061.0</td>\n",
       "<td>0.3786</td>\n",
       "<td> (7958.0/21019.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>82304.0</td>\n",
       "<td>37218.0</td>\n",
       "<td>0.2687</td>\n",
       "<td> (32115.0/119522.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  ------------------\n",
       "0      74346  24157  0.2452   (24157.0/98503.0)\n",
       "1      7958   13061  0.3786   (7958.0/21019.0)\n",
       "Total  82304  37218  0.2687   (32115.0/119522.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2144823</td>\n",
       "<td>0.4485465</td>\n",
       "<td>228.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1163590</td>\n",
       "<td>0.5950750</td>\n",
       "<td>304.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3176133</td>\n",
       "<td>0.4180092</td>\n",
       "<td>157.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4713304</td>\n",
       "<td>0.8307676</td>\n",
       "<td>85.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.8583979</td>\n",
       "<td>0.8734177</td>\n",
       "<td>8.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0178402</td>\n",
       "<td>1.0</td>\n",
       "<td>395.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9630204</td>\n",
       "<td>0.9999898</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2016418</td>\n",
       "<td>0.3093605</td>\n",
       "<td>237.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1853571</td>\n",
       "<td>0.6934205</td>\n",
       "<td>249.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1727500</td>\n",
       "<td>0.6962835</td>\n",
       "<td>259.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.214482     0.448546  228\n",
       "max f2                       0.116359     0.595075  304\n",
       "max f0point5                 0.317613     0.418009  157\n",
       "max accuracy                 0.47133      0.830768  85\n",
       "max precision                0.858398     0.873418  8\n",
       "max recall                   0.0178402    1         395\n",
       "max specificity              0.96302      0.99999   0\n",
       "max absolute_mcc             0.201642     0.30936   237\n",
       "max min_per_class_accuracy   0.185357     0.693421  249\n",
       "max mean_per_class_accuracy  0.17275      0.696283  259"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,59 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100065</td>\n",
       "<td>0.7214103</td>\n",
       "<td>5.6863790</td>\n",
       "<td>5.6863790</td>\n",
       "<td>1.0</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0569009</td>\n",
       "<td>0.0569009</td>\n",
       "<td>468.6378990</td>\n",
       "<td>468.6378990</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200047</td>\n",
       "<td>0.6275026</td>\n",
       "<td>5.6483112</td>\n",
       "<td>5.6673530</td>\n",
       "<td>0.9933054</td>\n",
       "<td>0.9966541</td>\n",
       "<td>0.0564727</td>\n",
       "<td>0.1133736</td>\n",
       "<td>464.8311181</td>\n",
       "<td>466.7353047</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300028</td>\n",
       "<td>0.5593015</td>\n",
       "<td>5.5531417</td>\n",
       "<td>5.6292932</td>\n",
       "<td>0.9765690</td>\n",
       "<td>0.9899610</td>\n",
       "<td>0.0555212</td>\n",
       "<td>0.1688948</td>\n",
       "<td>455.3141658</td>\n",
       "<td>462.9293200</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400010</td>\n",
       "<td>0.5001909</td>\n",
       "<td>5.3437687</td>\n",
       "<td>5.5579270</td>\n",
       "<td>0.9397490</td>\n",
       "<td>0.9774106</td>\n",
       "<td>0.0534279</td>\n",
       "<td>0.2223227</td>\n",
       "<td>434.3768708</td>\n",
       "<td>455.7927007</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500075</td>\n",
       "<td>0.4556617</td>\n",
       "<td>5.2822467</td>\n",
       "<td>5.5027633</td>\n",
       "<td>0.9289298</td>\n",
       "<td>0.9677096</td>\n",
       "<td>0.0528569</td>\n",
       "<td>0.2751796</td>\n",
       "<td>428.2246704</td>\n",
       "<td>450.2763273</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000067</td>\n",
       "<td>0.3563510</td>\n",
       "<td>3.7814040</td>\n",
       "<td>4.6421556</td>\n",
       "<td>0.6649933</td>\n",
       "<td>0.8163641</td>\n",
       "<td>0.1890670</td>\n",
       "<td>0.4642466</td>\n",
       "<td>278.1403967</td>\n",
       "<td>364.2155625</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500059</td>\n",
       "<td>0.3030485</td>\n",
       "<td>2.3541000</td>\n",
       "<td>3.8795130</td>\n",
       "<td>0.4139893</td>\n",
       "<td>0.6822466</td>\n",
       "<td>0.1177030</td>\n",
       "<td>0.5819497</td>\n",
       "<td>135.4100004</td>\n",
       "<td>287.9512957</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000050</td>\n",
       "<td>0.2649326</td>\n",
       "<td>1.6937340</td>\n",
       "<td>3.3330911</td>\n",
       "<td>0.2978581</td>\n",
       "<td>0.5861535</td>\n",
       "<td>0.0846853</td>\n",
       "<td>0.6666349</td>\n",
       "<td>69.3734037</td>\n",
       "<td>233.3091086</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.3000033</td>\n",
       "<td>0.2082362</td>\n",
       "<td>1.1237640</td>\n",
       "<td>2.5966693</td>\n",
       "<td>0.1976238</td>\n",
       "<td>0.4566472</td>\n",
       "<td>0.1123745</td>\n",
       "<td>0.7790095</td>\n",
       "<td>12.3763987</td>\n",
       "<td>159.6669258</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000017</td>\n",
       "<td>0.1628545</td>\n",
       "<td>0.7274493</td>\n",
       "<td>2.1293740</td>\n",
       "<td>0.1279284</td>\n",
       "<td>0.3744692</td>\n",
       "<td>0.0727437</td>\n",
       "<td>0.8517532</td>\n",
       "<td>-27.2550747</td>\n",
       "<td>112.9374031</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1261761</td>\n",
       "<td>0.5276267</td>\n",
       "<td>1.8090299</td>\n",
       "<td>0.0927878</td>\n",
       "<td>0.3181339</td>\n",
       "<td>0.0527618</td>\n",
       "<td>0.9045150</td>\n",
       "<td>-47.2373302</td>\n",
       "<td>80.9029925</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999983</td>\n",
       "<td>0.0999183</td>\n",
       "<td>0.4039270</td>\n",
       "<td>1.5748494</td>\n",
       "<td>0.0710341</td>\n",
       "<td>0.2769512</td>\n",
       "<td>0.0403920</td>\n",
       "<td>0.9449070</td>\n",
       "<td>-59.6072978</td>\n",
       "<td>57.4849374</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.6999967</td>\n",
       "<td>0.0821604</td>\n",
       "<td>0.2797516</td>\n",
       "<td>1.3898376</td>\n",
       "<td>0.0491968</td>\n",
       "<td>0.2444152</td>\n",
       "<td>0.0279747</td>\n",
       "<td>0.9728817</td>\n",
       "<td>-72.0248423</td>\n",
       "<td>38.9837614</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999950</td>\n",
       "<td>0.0696200</td>\n",
       "<td>0.1712765</td>\n",
       "<td>1.2375191</td>\n",
       "<td>0.0301205</td>\n",
       "<td>0.2176287</td>\n",
       "<td>0.0171274</td>\n",
       "<td>0.9900090</td>\n",
       "<td>-82.8723524</td>\n",
       "<td>23.7519065</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999933</td>\n",
       "<td>0.0557480</td>\n",
       "<td>0.0870655</td>\n",
       "<td>1.1096921</td>\n",
       "<td>0.0153112</td>\n",
       "<td>0.1951492</td>\n",
       "<td>0.0087064</td>\n",
       "<td>0.9987154</td>\n",
       "<td>-91.2934458</td>\n",
       "<td>10.9692084</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0056445</td>\n",
       "<td>0.0128447</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0022588</td>\n",
       "<td>0.1758588</td>\n",
       "<td>0.0012846</td>\n",
       "<td>1.0</td>\n",
       "<td>-98.7155339</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift       cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  ---------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100065                   0.72141            5.68638    5.68638            1                1                           0.0569009       0.0569009                  468.638   468.638\n",
       "    2        0.0200047                   0.627503           5.64831    5.66735            0.993305         0.996654                    0.0564727       0.113374                   464.831   466.735\n",
       "    3        0.0300028                   0.559302           5.55314    5.62929            0.976569         0.989961                    0.0555212       0.168895                   455.314   462.929\n",
       "    4        0.040001                    0.500191           5.34377    5.55793            0.939749         0.977411                    0.0534279       0.222323                   434.377   455.793\n",
       "    5        0.0500075                   0.455662           5.28225    5.50276            0.92893          0.96771                     0.0528569       0.27518                    428.225   450.276\n",
       "    6        0.100007                    0.356351           3.7814     4.64216            0.664993         0.816364                    0.189067        0.464247                   278.14    364.216\n",
       "    7        0.150006                    0.303049           2.3541     3.87951            0.413989         0.682247                    0.117703        0.58195                    135.41    287.951\n",
       "    8        0.200005                    0.264933           1.69373    3.33309            0.297858         0.586154                    0.0846853       0.666635                   69.3734   233.309\n",
       "    9        0.300003                    0.208236           1.12376    2.59667            0.197624         0.456647                    0.112375        0.779009                   12.3764   159.667\n",
       "    10       0.400002                    0.162854           0.727449   2.12937            0.127928         0.374469                    0.0727437       0.851753                   -27.2551  112.937\n",
       "    11       0.5                         0.126176           0.527627   1.80903            0.0927878        0.318134                    0.0527618       0.904515                   -47.2373  80.903\n",
       "    12       0.599998                    0.0999183          0.403927   1.57485            0.0710341        0.276951                    0.040392        0.944907                   -59.6073  57.4849\n",
       "    13       0.699997                    0.0821604          0.279752   1.38984            0.0491968        0.244415                    0.0279747       0.972882                   -72.0248  38.9838\n",
       "    14       0.799995                    0.06962            0.171276   1.23752            0.0301205        0.217629                    0.0171274       0.990009                   -82.8724  23.7519\n",
       "    15       0.899993                    0.055748           0.0870655  1.10969            0.0153112        0.195149                    0.00870641      0.998715                   -91.2934  10.9692\n",
       "    16       1                           0.00564454         0.0128447  1                  0.00225885       0.175859                    0.00128455      1                          -98.7155  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on validation data. **\n",
      "\n",
      "MSE: 0.1255647082935761\n",
      "RMSE: 0.3543511087799446\n",
      "LogLoss: 0.4005431746606248\n",
      "Mean Per-Class Error: 0.30165356027619683\n",
      "AUC: 0.763001806725211\n",
      "Gini: 0.526003613450422\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.2070602142049367: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>31178.0</td>\n",
       "<td>11009.0</td>\n",
       "<td>0.261</td>\n",
       "<td> (11009.0/42187.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>3214.0</td>\n",
       "<td>5823.0</td>\n",
       "<td>0.3556</td>\n",
       "<td> (3214.0/9037.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>34392.0</td>\n",
       "<td>16832.0</td>\n",
       "<td>0.2777</td>\n",
       "<td> (14223.0/51224.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  -----------------\n",
       "0      31178  11009  0.261    (11009.0/42187.0)\n",
       "1      3214   5823   0.3556   (3214.0/9037.0)\n",
       "Total  34392  16832  0.2777   (14223.0/51224.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2070602</td>\n",
       "<td>0.4501913</td>\n",
       "<td>222.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1225341</td>\n",
       "<td>0.5992234</td>\n",
       "<td>291.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3047351</td>\n",
       "<td>0.4191698</td>\n",
       "<td>154.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4671727</td>\n",
       "<td>0.8298454</td>\n",
       "<td>75.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.9359347</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0203794</td>\n",
       "<td>1.0</td>\n",
       "<td>393.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9359347</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2044848</td>\n",
       "<td>0.3112715</td>\n",
       "<td>224.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1871185</td>\n",
       "<td>0.6954275</td>\n",
       "<td>238.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1797217</td>\n",
       "<td>0.6983464</td>\n",
       "<td>243.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.20706      0.450191  222\n",
       "max f2                       0.122534     0.599223  291\n",
       "max f0point5                 0.304735     0.41917   154\n",
       "max accuracy                 0.467173     0.829845  75\n",
       "max precision                0.935935     1         0\n",
       "max recall                   0.0203794    1         393\n",
       "max specificity              0.935935     1         0\n",
       "max absolute_mcc             0.204485     0.311272  224\n",
       "max min_per_class_accuracy   0.187118     0.695428  238\n",
       "max mean_per_class_accuracy  0.179722     0.698346  243"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,64 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100148</td>\n",
       "<td>0.6049218</td>\n",
       "<td>4.1545088</td>\n",
       "<td>4.1545088</td>\n",
       "<td>0.7329435</td>\n",
       "<td>0.7329435</td>\n",
       "<td>0.0416067</td>\n",
       "<td>0.0416067</td>\n",
       "<td>315.4508830</td>\n",
       "<td>315.4508830</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200102</td>\n",
       "<td>0.5161323</td>\n",
       "<td>3.1441089</td>\n",
       "<td>3.6498018</td>\n",
       "<td>0.5546875</td>\n",
       "<td>0.6439024</td>\n",
       "<td>0.0314264</td>\n",
       "<td>0.0730331</td>\n",
       "<td>214.4108941</td>\n",
       "<td>264.9801763</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300055</td>\n",
       "<td>0.4657320</td>\n",
       "<td>2.9780468</td>\n",
       "<td>3.4260291</td>\n",
       "<td>0.5253906</td>\n",
       "<td>0.6044242</td>\n",
       "<td>0.0297665</td>\n",
       "<td>0.1027996</td>\n",
       "<td>197.8046849</td>\n",
       "<td>242.6029144</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400008</td>\n",
       "<td>0.4348848</td>\n",
       "<td>2.7234183</td>\n",
       "<td>3.2504622</td>\n",
       "<td>0.4804688</td>\n",
       "<td>0.5734505</td>\n",
       "<td>0.0272214</td>\n",
       "<td>0.1300210</td>\n",
       "<td>172.3418308</td>\n",
       "<td>225.0462161</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500156</td>\n",
       "<td>0.4117492</td>\n",
       "<td>2.3203374</td>\n",
       "<td>3.0642194</td>\n",
       "<td>0.4093567</td>\n",
       "<td>0.5405933</td>\n",
       "<td>0.0232378</td>\n",
       "<td>0.1532588</td>\n",
       "<td>132.0337378</td>\n",
       "<td>206.4219377</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000117</td>\n",
       "<td>0.3503748</td>\n",
       "<td>2.2708424</td>\n",
       "<td>2.6676083</td>\n",
       "<td>0.4006248</td>\n",
       "<td>0.4706227</td>\n",
       "<td>0.1135333</td>\n",
       "<td>0.2667921</td>\n",
       "<td>127.0842370</td>\n",
       "<td>166.7608306</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500078</td>\n",
       "<td>0.3065046</td>\n",
       "<td>2.0340196</td>\n",
       "<td>2.4564396</td>\n",
       "<td>0.3588442</td>\n",
       "<td>0.4333680</td>\n",
       "<td>0.1016930</td>\n",
       "<td>0.3684851</td>\n",
       "<td>103.4019628</td>\n",
       "<td>145.6439565</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000039</td>\n",
       "<td>0.2728133</td>\n",
       "<td>1.7263714</td>\n",
       "<td>2.2739403</td>\n",
       "<td>0.3045685</td>\n",
       "<td>0.4011713</td>\n",
       "<td>0.0863118</td>\n",
       "<td>0.4547969</td>\n",
       "<td>72.6371393</td>\n",
       "<td>127.3940337</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.2999961</td>\n",
       "<td>0.2201204</td>\n",
       "<td>1.5094683</td>\n",
       "<td>2.0191329</td>\n",
       "<td>0.2663022</td>\n",
       "<td>0.3562179</td>\n",
       "<td>0.1509350</td>\n",
       "<td>0.6057320</td>\n",
       "<td>50.9468320</td>\n",
       "<td>101.9132914</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000078</td>\n",
       "<td>0.1748262</td>\n",
       "<td>1.1938405</td>\n",
       "<td>1.8127897</td>\n",
       "<td>0.2106188</td>\n",
       "<td>0.3198145</td>\n",
       "<td>0.1193980</td>\n",
       "<td>0.7251300</td>\n",
       "<td>19.3840466</td>\n",
       "<td>81.2789663</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1365017</td>\n",
       "<td>0.8919586</td>\n",
       "<td>1.6286378</td>\n",
       "<td>0.1573604</td>\n",
       "<td>0.2873263</td>\n",
       "<td>0.0891889</td>\n",
       "<td>0.8143189</td>\n",
       "<td>-10.8041447</td>\n",
       "<td>62.8637822</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999922</td>\n",
       "<td>0.1058379</td>\n",
       "<td>0.6717355</td>\n",
       "<td>1.4691645</td>\n",
       "<td>0.1185084</td>\n",
       "<td>0.2591918</td>\n",
       "<td>0.0671683</td>\n",
       "<td>0.8814872</td>\n",
       "<td>-32.8264465</td>\n",
       "<td>46.9164486</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.7000039</td>\n",
       "<td>0.0851639</td>\n",
       "<td>0.4669144</td>\n",
       "<td>1.3259699</td>\n",
       "<td>0.0823736</td>\n",
       "<td>0.2339292</td>\n",
       "<td>0.0466969</td>\n",
       "<td>0.9281841</td>\n",
       "<td>-53.3085564</td>\n",
       "<td>32.5969935</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999961</td>\n",
       "<td>0.0716401</td>\n",
       "<td>0.3740471</td>\n",
       "<td>1.2069883</td>\n",
       "<td>0.0659898</td>\n",
       "<td>0.2129383</td>\n",
       "<td>0.0374018</td>\n",
       "<td>0.9655859</td>\n",
       "<td>-62.5952865</td>\n",
       "<td>20.6988296</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999883</td>\n",
       "<td>0.0578111</td>\n",
       "<td>0.2346094</td>\n",
       "<td>1.0989532</td>\n",
       "<td>0.0413901</td>\n",
       "<td>0.1938787</td>\n",
       "<td>0.0234591</td>\n",
       "<td>0.9890450</td>\n",
       "<td>-76.5390554</td>\n",
       "<td>9.8953233</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0055948</td>\n",
       "<td>0.1095368</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0193246</td>\n",
       "<td>0.1764212</td>\n",
       "<td>0.0109550</td>\n",
       "<td>1.0</td>\n",
       "<td>-89.0463201</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift      cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  --------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100148                   0.604922           4.15451   4.15451            0.732943         0.732943                    0.0416067       0.0416067                  315.451   315.451\n",
       "    2        0.0200102                   0.516132           3.14411   3.6498             0.554688         0.643902                    0.0314264       0.0730331                  214.411   264.98\n",
       "    3        0.0300055                   0.465732           2.97805   3.42603            0.525391         0.604424                    0.0297665       0.1028                     197.805   242.603\n",
       "    4        0.0400008                   0.434885           2.72342   3.25046            0.480469         0.57345                     0.0272214       0.130021                   172.342   225.046\n",
       "    5        0.0500156                   0.411749           2.32034   3.06422            0.409357         0.540593                    0.0232378       0.153259                   132.034   206.422\n",
       "    6        0.100012                    0.350375           2.27084   2.66761            0.400625         0.470623                    0.113533        0.266792                   127.084   166.761\n",
       "    7        0.150008                    0.306505           2.03402   2.45644            0.358844         0.433368                    0.101693        0.368485                   103.402   145.644\n",
       "    8        0.200004                    0.272813           1.72637   2.27394            0.304569         0.401171                    0.0863118       0.454797                   72.6371   127.394\n",
       "    9        0.299996                    0.22012            1.50947   2.01913            0.266302         0.356218                    0.150935        0.605732                   50.9468   101.913\n",
       "    10       0.400008                    0.174826           1.19384   1.81279            0.210619         0.319815                    0.119398        0.72513                    19.384    81.279\n",
       "    11       0.5                         0.136502           0.891959  1.62864            0.15736          0.287326                    0.0891889       0.814319                   -10.8041  62.8638\n",
       "    12       0.599992                    0.105838           0.671736  1.46916            0.118508         0.259192                    0.0671683       0.881487                   -32.8264  46.9164\n",
       "    13       0.700004                    0.0851639          0.466914  1.32597            0.0823736        0.233929                    0.0466969       0.928184                   -53.3086  32.597\n",
       "    14       0.799996                    0.0716401          0.374047  1.20699            0.0659898        0.212938                    0.0374018       0.965586                   -62.5953  20.6988\n",
       "    15       0.899988                    0.0578111          0.234609  1.09895            0.0413901        0.193879                    0.0234591       0.989045                   -76.5391  9.89532\n",
       "    16       1                           0.00559479         0.109537  1                  0.0193246        0.176421                    0.010955        1                          -89.0463  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Scoring History: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>timestamp</b></td>\n",
       "<td><b>duration</b></td>\n",
       "<td><b>number_of_trees</b></td>\n",
       "<td><b>training_rmse</b></td>\n",
       "<td><b>training_logloss</b></td>\n",
       "<td><b>training_auc</b></td>\n",
       "<td><b>training_lift</b></td>\n",
       "<td><b>training_classification_error</b></td>\n",
       "<td><b>validation_rmse</b></td>\n",
       "<td><b>validation_logloss</b></td>\n",
       "<td><b>validation_auc</b></td>\n",
       "<td><b>validation_lift</b></td>\n",
       "<td><b>validation_classification_error</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:20:53</td>\n",
       "<td> 0.507 sec</td>\n",
       "<td>0.0</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:21:09</td>\n",
       "<td>17.067 sec</td>\n",
       "<td>100.0</td>\n",
       "<td>0.3551600</td>\n",
       "<td>0.4028102</td>\n",
       "<td>0.7559429</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2773632</td>\n",
       "<td>0.3546847</td>\n",
       "<td>0.4013012</td>\n",
       "<td>0.7610853</td>\n",
       "<td>4.0550658</td>\n",
       "<td>0.2774871</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:21:36</td>\n",
       "<td>44.241 sec</td>\n",
       "<td>200.0</td>\n",
       "<td>0.3546097</td>\n",
       "<td>0.4016807</td>\n",
       "<td>0.7584293</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2738910</td>\n",
       "<td>0.3545292</td>\n",
       "<td>0.4009644</td>\n",
       "<td>0.7619967</td>\n",
       "<td>4.1103119</td>\n",
       "<td>0.2756520</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:22:15</td>\n",
       "<td> 1 min 23.477 sec</td>\n",
       "<td>300.0</td>\n",
       "<td>0.3544307</td>\n",
       "<td>0.4013222</td>\n",
       "<td>0.7592525</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2661518</td>\n",
       "<td>0.3544294</td>\n",
       "<td>0.4007347</td>\n",
       "<td>0.7625247</td>\n",
       "<td>4.1324104</td>\n",
       "<td>0.2806497</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:23:09</td>\n",
       "<td> 2 min 16.563 sec</td>\n",
       "<td>400.0</td>\n",
       "<td>0.3542955</td>\n",
       "<td>0.4010123</td>\n",
       "<td>0.7598601</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2741838</td>\n",
       "<td>0.3543655</td>\n",
       "<td>0.4005885</td>\n",
       "<td>0.7627619</td>\n",
       "<td>4.1434596</td>\n",
       "<td>0.2802593</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:24:16</td>\n",
       "<td> 3 min 23.899 sec</td>\n",
       "<td>500.0</td>\n",
       "<td>0.3542421</td>\n",
       "<td>0.4009071</td>\n",
       "<td>0.7600818</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2720336</td>\n",
       "<td>0.3543676</td>\n",
       "<td>0.4005762</td>\n",
       "<td>0.7628463</td>\n",
       "<td>4.1655581</td>\n",
       "<td>0.2790294</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:25:39</td>\n",
       "<td> 4 min 46.709 sec</td>\n",
       "<td>600.0</td>\n",
       "<td>0.3542157</td>\n",
       "<td>0.4008344</td>\n",
       "<td>0.7602705</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2614498</td>\n",
       "<td>0.3543582</td>\n",
       "<td>0.4005482</td>\n",
       "<td>0.7629427</td>\n",
       "<td>4.1876565</td>\n",
       "<td>0.2787756</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:27:18</td>\n",
       "<td> 6 min 25.601 sec</td>\n",
       "<td>700.0</td>\n",
       "<td>0.3541845</td>\n",
       "<td>0.4007659</td>\n",
       "<td>0.7604756</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2750205</td>\n",
       "<td>0.3543425</td>\n",
       "<td>0.4005276</td>\n",
       "<td>0.7630291</td>\n",
       "<td>4.1876565</td>\n",
       "<td>0.2822700</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:29:11</td>\n",
       "<td> 8 min 19.008 sec</td>\n",
       "<td>800.0</td>\n",
       "<td>0.3541727</td>\n",
       "<td>0.4007398</td>\n",
       "<td>0.7605263</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2686953</td>\n",
       "<td>0.3543511</td>\n",
       "<td>0.4005432</td>\n",
       "<td>0.7630018</td>\n",
       "<td>4.1545088</td>\n",
       "<td>0.2776628</td></tr></table></div>"
      ],
      "text/plain": [
       "    timestamp            duration          number_of_trees    training_rmse    training_logloss    training_auc    training_lift    training_classification_error    validation_rmse    validation_logloss    validation_auc    validation_lift    validation_classification_error\n",
       "--  -------------------  ----------------  -----------------  ---------------  ------------------  --------------  ---------------  -------------------------------  -----------------  --------------------  ----------------  -----------------  ---------------------------------\n",
       "    2017-07-12 22:20:53  0.507 sec         0                  nan              nan                 nan             nan              nan                              nan                nan                   nan               nan                nan\n",
       "    2017-07-12 22:21:09  17.067 sec        100                0.35516          0.40281             0.755943        5.68638          0.277363                         0.354685           0.401301              0.761085          4.05507            0.277487\n",
       "    2017-07-12 22:21:36  44.241 sec        200                0.35461          0.401681            0.758429        5.68638          0.273891                         0.354529           0.400964              0.761997          4.11031            0.275652\n",
       "    2017-07-12 22:22:15  1 min 23.477 sec  300                0.354431         0.401322            0.759252        5.68638          0.266152                         0.354429           0.400735              0.762525          4.13241            0.28065\n",
       "    2017-07-12 22:23:09  2 min 16.563 sec  400                0.354295         0.401012            0.75986         5.68638          0.274184                         0.354365           0.400589              0.762762          4.14346            0.280259\n",
       "    2017-07-12 22:24:16  3 min 23.899 sec  500                0.354242         0.400907            0.760082        5.68638          0.272034                         0.354368           0.400576              0.762846          4.16556            0.279029\n",
       "    2017-07-12 22:25:39  4 min 46.709 sec  600                0.354216         0.400834            0.76027         5.68638          0.26145                          0.354358           0.400548              0.762943          4.18766            0.278776\n",
       "    2017-07-12 22:27:18  6 min 25.601 sec  700                0.354185         0.400766            0.760476        5.68638          0.27502                          0.354343           0.400528              0.763029          4.18766            0.28227\n",
       "    2017-07-12 22:29:11  8 min 19.008 sec  800                0.354173         0.40074             0.760526        5.68638          0.268695                         0.354351           0.400543              0.763002          4.15451            0.277663"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable Importances: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>variable</b></td>\n",
       "<td><b>relative_importance</b></td>\n",
       "<td><b>scaled_importance</b></td>\n",
       "<td><b>percentage</b></td></tr>\n",
       "<tr><td>living_region</td>\n",
       "<td>515209.3125000</td>\n",
       "<td>1.0</td>\n",
       "<td>0.1952278</td></tr>\n",
       "<tr><td>tariff_id</td>\n",
       "<td>502785.1562500</td>\n",
       "<td>0.9758852</td>\n",
       "<td>0.1905199</td></tr>\n",
       "<tr><td>credit_sum</td>\n",
       "<td>219592.2187500</td>\n",
       "<td>0.4262194</td>\n",
       "<td>0.0832099</td></tr>\n",
       "<tr><td>credit_month</td>\n",
       "<td>199588.3593750</td>\n",
       "<td>0.3873928</td>\n",
       "<td>0.0756298</td></tr>\n",
       "<tr><td>age</td>\n",
       "<td>192851.4062500</td>\n",
       "<td>0.3743166</td>\n",
       "<td>0.0730770</td></tr>\n",
       "<tr><td>score_shk</td>\n",
       "<td>181426.1875000</td>\n",
       "<td>0.3521407</td>\n",
       "<td>0.0687477</td></tr>\n",
       "<tr><td>job_position</td>\n",
       "<td>149373.0937500</td>\n",
       "<td>0.2899270</td>\n",
       "<td>0.0566018</td></tr>\n",
       "<tr><td>credit_count</td>\n",
       "<td>126724.2968750</td>\n",
       "<td>0.2459666</td>\n",
       "<td>0.0480195</td></tr>\n",
       "<tr><td>overdue_credit_count</td>\n",
       "<td>112300.5390625</td>\n",
       "<td>0.2179707</td>\n",
       "<td>0.0425539</td></tr>\n",
       "<tr><td>education</td>\n",
       "<td>90957.6406250</td>\n",
       "<td>0.1765450</td>\n",
       "<td>0.0344665</td></tr>\n",
       "<tr><td>okrug</td>\n",
       "<td>88394.7890625</td>\n",
       "<td>0.1715706</td>\n",
       "<td>0.0334954</td></tr>\n",
       "<tr><td>marital_status</td>\n",
       "<td>80072.0546875</td>\n",
       "<td>0.1554166</td>\n",
       "<td>0.0303416</td></tr>\n",
       "<tr><td>monthly_income</td>\n",
       "<td>78311.375</td>\n",
       "<td>0.1519991</td>\n",
       "<td>0.0296745</td></tr>\n",
       "<tr><td>avregzarplata</td>\n",
       "<td>60994.9648438</td>\n",
       "<td>0.1183887</td>\n",
       "<td>0.0231128</td></tr>\n",
       "<tr><td>gender</td>\n",
       "<td>40435.0156250</td>\n",
       "<td>0.0784827</td>\n",
       "<td>0.0153220</td></tr></table></div>"
      ],
      "text/plain": [
       "variable              relative_importance    scaled_importance    percentage\n",
       "--------------------  ---------------------  -------------------  ------------\n",
       "living_region         515209                 1                    0.195228\n",
       "tariff_id             502785                 0.975885             0.19052\n",
       "credit_sum            219592                 0.426219             0.0832099\n",
       "credit_month          199588                 0.387393             0.0756298\n",
       "age                   192851                 0.374317             0.073077\n",
       "score_shk             181426                 0.352141             0.0687477\n",
       "job_position          149373                 0.289927             0.0566018\n",
       "credit_count          126724                 0.245967             0.0480195\n",
       "overdue_credit_count  112301                 0.217971             0.0425539\n",
       "education             90957.6                0.176545             0.0344665\n",
       "okrug                 88394.8                0.171571             0.0334954\n",
       "marital_status        80072.1                0.155417             0.0303416\n",
       "monthly_income        78311.4                0.151999             0.0296745\n",
       "avregzarplata         60995                  0.118389             0.0231128\n",
       "gender                40435                  0.0784827            0.015322"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "drf prediction progress: |████████████████████████████████████████████████| 100%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th style=\"text-align: right;\">  predict</th><th style=\"text-align: right;\">      p0</th><th style=\"text-align: right;\">       p1</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.902126</td><td style=\"text-align: right;\">0.0978736</td></tr>\n",
       "<tr><td style=\"text-align: right;\">        1</td><td style=\"text-align: right;\">0.724976</td><td style=\"text-align: right;\">0.275024 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        1</td><td style=\"text-align: right;\">0.739505</td><td style=\"text-align: right;\">0.260495 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.918747</td><td style=\"text-align: right;\">0.0812526</td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.928387</td><td style=\"text-align: right;\">0.0716131</td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.931632</td><td style=\"text-align: right;\">0.0683684</td></tr>\n",
       "<tr><td style=\"text-align: right;\">        1</td><td style=\"text-align: right;\">0.660208</td><td style=\"text-align: right;\">0.339792 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.822169</td><td style=\"text-align: right;\">0.177831 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.811354</td><td style=\"text-align: right;\">0.188646 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.833697</td><td style=\"text-align: right;\">0.166303 </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions = rf1.predict(validation)\n",
    "predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Export File progress: |███████████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "h2o.export_file(predictions, path = \"C:\\\\Trees\\\\pred.csv\", force=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cd1d1e3470>"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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aGYTFYgEAGAwGv+tGoxGnTp0KeE9bWxvq6+sxYsQI3HPPPUhOTsbJkyfx1ltv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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cd1d2164a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp = rf1.roc(valid=True)\n",
    "df = pd.DataFrame({\"false positive rate\": tmp[0], \"true positive rate\": tmp[1]})\n",
    "df.plot(kind = \"scatter\", x = \"false positive rate\", y = \"true positive rate\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1cc20d80518>"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1uN3ufIdprrrqKsqXL8+cOXOYOnUqderU4f777+fyyy/3OocEFrtvN/aT8ZiO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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ccf99a9c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(tmp[0], tmp[1], label=\"ROC-кривая для модели rf1(контроль)\")\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR (полнота)\")\n",
    "plt.legend(loc=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Сохранение модели случайного леса, построенной с помощью класса H2ORandomForestEstimator, и применение к новым данным"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Trees\\\\mybest_model\\\\RF_credit'"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h2o.save_model(rf1, path=\"C:\\\\Trees\\\\mybest_model\", force=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "savedmodel=h2o.load_model(path=\"C:\\\\Trees\\\\mybest_model\\\\RF_credit\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Details\n",
      "=============\n",
      "H2ORandomForestEstimator :  Distributed Random Forest\n",
      "Model Key:  RF_credit\n",
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on train data. **\n",
      "\n",
      "MSE: 0.12543831753065773\n",
      "RMSE: 0.35417272273660166\n",
      "LogLoss: 0.4007397887502991\n",
      "Mean Per-Class Error: 0.3037165105624732\n",
      "AUC: 0.7605262775277374\n",
      "Gini: 0.5210525550554748\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21448232967695893: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>74346.0</td>\n",
       "<td>24157.0</td>\n",
       "<td>0.2452</td>\n",
       "<td> (24157.0/98503.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>7958.0</td>\n",
       "<td>13061.0</td>\n",
       "<td>0.3786</td>\n",
       "<td> (7958.0/21019.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>82304.0</td>\n",
       "<td>37218.0</td>\n",
       "<td>0.2687</td>\n",
       "<td> (32115.0/119522.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  ------------------\n",
       "0      74346  24157  0.2452   (24157.0/98503.0)\n",
       "1      7958   13061  0.3786   (7958.0/21019.0)\n",
       "Total  82304  37218  0.2687   (32115.0/119522.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2144823</td>\n",
       "<td>0.4485465</td>\n",
       "<td>228.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1163590</td>\n",
       "<td>0.5950750</td>\n",
       "<td>304.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3176133</td>\n",
       "<td>0.4180092</td>\n",
       "<td>157.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4713304</td>\n",
       "<td>0.8307676</td>\n",
       "<td>85.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.8583979</td>\n",
       "<td>0.8734177</td>\n",
       "<td>8.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0178402</td>\n",
       "<td>1.0</td>\n",
       "<td>395.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9630204</td>\n",
       "<td>0.9999898</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2016418</td>\n",
       "<td>0.3093605</td>\n",
       "<td>237.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1853571</td>\n",
       "<td>0.6934205</td>\n",
       "<td>249.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1727500</td>\n",
       "<td>0.6962835</td>\n",
       "<td>259.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.214482     0.448546  228\n",
       "max f2                       0.116359     0.595075  304\n",
       "max f0point5                 0.317613     0.418009  157\n",
       "max accuracy                 0.47133      0.830768  85\n",
       "max precision                0.858398     0.873418  8\n",
       "max recall                   0.0178402    1         395\n",
       "max specificity              0.96302      0.99999   0\n",
       "max absolute_mcc             0.201642     0.30936   237\n",
       "max min_per_class_accuracy   0.185357     0.693421  249\n",
       "max mean_per_class_accuracy  0.17275      0.696283  259"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,59 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100065</td>\n",
       "<td>0.7214103</td>\n",
       "<td>5.6863790</td>\n",
       "<td>5.6863790</td>\n",
       "<td>1.0</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0569009</td>\n",
       "<td>0.0569009</td>\n",
       "<td>468.6378990</td>\n",
       "<td>468.6378990</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200047</td>\n",
       "<td>0.6275026</td>\n",
       "<td>5.6483112</td>\n",
       "<td>5.6673530</td>\n",
       "<td>0.9933054</td>\n",
       "<td>0.9966541</td>\n",
       "<td>0.0564727</td>\n",
       "<td>0.1133736</td>\n",
       "<td>464.8311181</td>\n",
       "<td>466.7353047</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300028</td>\n",
       "<td>0.5593015</td>\n",
       "<td>5.5531417</td>\n",
       "<td>5.6292932</td>\n",
       "<td>0.9765690</td>\n",
       "<td>0.9899610</td>\n",
       "<td>0.0555212</td>\n",
       "<td>0.1688948</td>\n",
       "<td>455.3141658</td>\n",
       "<td>462.9293200</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400010</td>\n",
       "<td>0.5001909</td>\n",
       "<td>5.3437687</td>\n",
       "<td>5.5579270</td>\n",
       "<td>0.9397490</td>\n",
       "<td>0.9774106</td>\n",
       "<td>0.0534279</td>\n",
       "<td>0.2223227</td>\n",
       "<td>434.3768708</td>\n",
       "<td>455.7927007</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500075</td>\n",
       "<td>0.4556617</td>\n",
       "<td>5.2822467</td>\n",
       "<td>5.5027633</td>\n",
       "<td>0.9289298</td>\n",
       "<td>0.9677096</td>\n",
       "<td>0.0528569</td>\n",
       "<td>0.2751796</td>\n",
       "<td>428.2246704</td>\n",
       "<td>450.2763273</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000067</td>\n",
       "<td>0.3563510</td>\n",
       "<td>3.7814040</td>\n",
       "<td>4.6421556</td>\n",
       "<td>0.6649933</td>\n",
       "<td>0.8163641</td>\n",
       "<td>0.1890670</td>\n",
       "<td>0.4642466</td>\n",
       "<td>278.1403967</td>\n",
       "<td>364.2155625</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500059</td>\n",
       "<td>0.3030485</td>\n",
       "<td>2.3541000</td>\n",
       "<td>3.8795130</td>\n",
       "<td>0.4139893</td>\n",
       "<td>0.6822466</td>\n",
       "<td>0.1177030</td>\n",
       "<td>0.5819497</td>\n",
       "<td>135.4100004</td>\n",
       "<td>287.9512957</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000050</td>\n",
       "<td>0.2649326</td>\n",
       "<td>1.6937340</td>\n",
       "<td>3.3330911</td>\n",
       "<td>0.2978581</td>\n",
       "<td>0.5861535</td>\n",
       "<td>0.0846853</td>\n",
       "<td>0.6666349</td>\n",
       "<td>69.3734037</td>\n",
       "<td>233.3091086</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.3000033</td>\n",
       "<td>0.2082362</td>\n",
       "<td>1.1237640</td>\n",
       "<td>2.5966693</td>\n",
       "<td>0.1976238</td>\n",
       "<td>0.4566472</td>\n",
       "<td>0.1123745</td>\n",
       "<td>0.7790095</td>\n",
       "<td>12.3763987</td>\n",
       "<td>159.6669258</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000017</td>\n",
       "<td>0.1628545</td>\n",
       "<td>0.7274493</td>\n",
       "<td>2.1293740</td>\n",
       "<td>0.1279284</td>\n",
       "<td>0.3744692</td>\n",
       "<td>0.0727437</td>\n",
       "<td>0.8517532</td>\n",
       "<td>-27.2550747</td>\n",
       "<td>112.9374031</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1261761</td>\n",
       "<td>0.5276267</td>\n",
       "<td>1.8090299</td>\n",
       "<td>0.0927878</td>\n",
       "<td>0.3181339</td>\n",
       "<td>0.0527618</td>\n",
       "<td>0.9045150</td>\n",
       "<td>-47.2373302</td>\n",
       "<td>80.9029925</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999983</td>\n",
       "<td>0.0999183</td>\n",
       "<td>0.4039270</td>\n",
       "<td>1.5748494</td>\n",
       "<td>0.0710341</td>\n",
       "<td>0.2769512</td>\n",
       "<td>0.0403920</td>\n",
       "<td>0.9449070</td>\n",
       "<td>-59.6072978</td>\n",
       "<td>57.4849374</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.6999967</td>\n",
       "<td>0.0821604</td>\n",
       "<td>0.2797516</td>\n",
       "<td>1.3898376</td>\n",
       "<td>0.0491968</td>\n",
       "<td>0.2444152</td>\n",
       "<td>0.0279747</td>\n",
       "<td>0.9728817</td>\n",
       "<td>-72.0248423</td>\n",
       "<td>38.9837614</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999950</td>\n",
       "<td>0.0696200</td>\n",
       "<td>0.1712765</td>\n",
       "<td>1.2375191</td>\n",
       "<td>0.0301205</td>\n",
       "<td>0.2176287</td>\n",
       "<td>0.0171274</td>\n",
       "<td>0.9900090</td>\n",
       "<td>-82.8723524</td>\n",
       "<td>23.7519065</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999933</td>\n",
       "<td>0.0557480</td>\n",
       "<td>0.0870655</td>\n",
       "<td>1.1096921</td>\n",
       "<td>0.0153112</td>\n",
       "<td>0.1951492</td>\n",
       "<td>0.0087064</td>\n",
       "<td>0.9987154</td>\n",
       "<td>-91.2934458</td>\n",
       "<td>10.9692084</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0056445</td>\n",
       "<td>0.0128447</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0022588</td>\n",
       "<td>0.1758588</td>\n",
       "<td>0.0012846</td>\n",
       "<td>1.0</td>\n",
       "<td>-98.7155339</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift       cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  ---------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100065                   0.72141            5.68638    5.68638            1                1                           0.0569009       0.0569009                  468.638   468.638\n",
       "    2        0.0200047                   0.627503           5.64831    5.66735            0.993305         0.996654                    0.0564727       0.113374                   464.831   466.735\n",
       "    3        0.0300028                   0.559302           5.55314    5.62929            0.976569         0.989961                    0.0555212       0.168895                   455.314   462.929\n",
       "    4        0.040001                    0.500191           5.34377    5.55793            0.939749         0.977411                    0.0534279       0.222323                   434.377   455.793\n",
       "    5        0.0500075                   0.455662           5.28225    5.50276            0.92893          0.96771                     0.0528569       0.27518                    428.225   450.276\n",
       "    6        0.100007                    0.356351           3.7814     4.64216            0.664993         0.816364                    0.189067        0.464247                   278.14    364.216\n",
       "    7        0.150006                    0.303049           2.3541     3.87951            0.413989         0.682247                    0.117703        0.58195                    135.41    287.951\n",
       "    8        0.200005                    0.264933           1.69373    3.33309            0.297858         0.586154                    0.0846853       0.666635                   69.3734   233.309\n",
       "    9        0.300003                    0.208236           1.12376    2.59667            0.197624         0.456647                    0.112375        0.779009                   12.3764   159.667\n",
       "    10       0.400002                    0.162854           0.727449   2.12937            0.127928         0.374469                    0.0727437       0.851753                   -27.2551  112.937\n",
       "    11       0.5                         0.126176           0.527627   1.80903            0.0927878        0.318134                    0.0527618       0.904515                   -47.2373  80.903\n",
       "    12       0.599998                    0.0999183          0.403927   1.57485            0.0710341        0.276951                    0.040392        0.944907                   -59.6073  57.4849\n",
       "    13       0.699997                    0.0821604          0.279752   1.38984            0.0491968        0.244415                    0.0279747       0.972882                   -72.0248  38.9838\n",
       "    14       0.799995                    0.06962            0.171276   1.23752            0.0301205        0.217629                    0.0171274       0.990009                   -82.8724  23.7519\n",
       "    15       0.899993                    0.055748           0.0870655  1.10969            0.0153112        0.195149                    0.00870641      0.998715                   -91.2934  10.9692\n",
       "    16       1                           0.00564454         0.0128447  1                  0.00225885       0.175859                    0.00128455      1                          -98.7155  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on validation data. **\n",
      "\n",
      "MSE: 0.1255647082935761\n",
      "RMSE: 0.3543511087799446\n",
      "LogLoss: 0.4005431746606248\n",
      "Mean Per-Class Error: 0.30165356027619683\n",
      "AUC: 0.763001806725211\n",
      "Gini: 0.526003613450422\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.2070602142049367: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>31178.0</td>\n",
       "<td>11009.0</td>\n",
       "<td>0.261</td>\n",
       "<td> (11009.0/42187.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>3214.0</td>\n",
       "<td>5823.0</td>\n",
       "<td>0.3556</td>\n",
       "<td> (3214.0/9037.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>34392.0</td>\n",
       "<td>16832.0</td>\n",
       "<td>0.2777</td>\n",
       "<td> (14223.0/51224.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  -----------------\n",
       "0      31178  11009  0.261    (11009.0/42187.0)\n",
       "1      3214   5823   0.3556   (3214.0/9037.0)\n",
       "Total  34392  16832  0.2777   (14223.0/51224.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2070602</td>\n",
       "<td>0.4501913</td>\n",
       "<td>222.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1225341</td>\n",
       "<td>0.5992234</td>\n",
       "<td>291.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3047351</td>\n",
       "<td>0.4191698</td>\n",
       "<td>154.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4671727</td>\n",
       "<td>0.8298454</td>\n",
       "<td>75.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.9359347</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0203794</td>\n",
       "<td>1.0</td>\n",
       "<td>393.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9359347</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2044848</td>\n",
       "<td>0.3112715</td>\n",
       "<td>224.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1871185</td>\n",
       "<td>0.6954275</td>\n",
       "<td>238.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1797217</td>\n",
       "<td>0.6983464</td>\n",
       "<td>243.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.20706      0.450191  222\n",
       "max f2                       0.122534     0.599223  291\n",
       "max f0point5                 0.304735     0.41917   154\n",
       "max accuracy                 0.467173     0.829845  75\n",
       "max precision                0.935935     1         0\n",
       "max recall                   0.0203794    1         393\n",
       "max specificity              0.935935     1         0\n",
       "max absolute_mcc             0.204485     0.311272  224\n",
       "max min_per_class_accuracy   0.187118     0.695428  238\n",
       "max mean_per_class_accuracy  0.179722     0.698346  243"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,64 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100148</td>\n",
       "<td>0.6049218</td>\n",
       "<td>4.1545088</td>\n",
       "<td>4.1545088</td>\n",
       "<td>0.7329435</td>\n",
       "<td>0.7329435</td>\n",
       "<td>0.0416067</td>\n",
       "<td>0.0416067</td>\n",
       "<td>315.4508830</td>\n",
       "<td>315.4508830</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200102</td>\n",
       "<td>0.5161323</td>\n",
       "<td>3.1441089</td>\n",
       "<td>3.6498018</td>\n",
       "<td>0.5546875</td>\n",
       "<td>0.6439024</td>\n",
       "<td>0.0314264</td>\n",
       "<td>0.0730331</td>\n",
       "<td>214.4108941</td>\n",
       "<td>264.9801763</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300055</td>\n",
       "<td>0.4657320</td>\n",
       "<td>2.9780468</td>\n",
       "<td>3.4260291</td>\n",
       "<td>0.5253906</td>\n",
       "<td>0.6044242</td>\n",
       "<td>0.0297665</td>\n",
       "<td>0.1027996</td>\n",
       "<td>197.8046849</td>\n",
       "<td>242.6029144</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400008</td>\n",
       "<td>0.4348848</td>\n",
       "<td>2.7234183</td>\n",
       "<td>3.2504622</td>\n",
       "<td>0.4804688</td>\n",
       "<td>0.5734505</td>\n",
       "<td>0.0272214</td>\n",
       "<td>0.1300210</td>\n",
       "<td>172.3418308</td>\n",
       "<td>225.0462161</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500156</td>\n",
       "<td>0.4117492</td>\n",
       "<td>2.3203374</td>\n",
       "<td>3.0642194</td>\n",
       "<td>0.4093567</td>\n",
       "<td>0.5405933</td>\n",
       "<td>0.0232378</td>\n",
       "<td>0.1532588</td>\n",
       "<td>132.0337378</td>\n",
       "<td>206.4219377</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000117</td>\n",
       "<td>0.3503748</td>\n",
       "<td>2.2708424</td>\n",
       "<td>2.6676083</td>\n",
       "<td>0.4006248</td>\n",
       "<td>0.4706227</td>\n",
       "<td>0.1135333</td>\n",
       "<td>0.2667921</td>\n",
       "<td>127.0842370</td>\n",
       "<td>166.7608306</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500078</td>\n",
       "<td>0.3065046</td>\n",
       "<td>2.0340196</td>\n",
       "<td>2.4564396</td>\n",
       "<td>0.3588442</td>\n",
       "<td>0.4333680</td>\n",
       "<td>0.1016930</td>\n",
       "<td>0.3684851</td>\n",
       "<td>103.4019628</td>\n",
       "<td>145.6439565</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000039</td>\n",
       "<td>0.2728133</td>\n",
       "<td>1.7263714</td>\n",
       "<td>2.2739403</td>\n",
       "<td>0.3045685</td>\n",
       "<td>0.4011713</td>\n",
       "<td>0.0863118</td>\n",
       "<td>0.4547969</td>\n",
       "<td>72.6371393</td>\n",
       "<td>127.3940337</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.2999961</td>\n",
       "<td>0.2201204</td>\n",
       "<td>1.5094683</td>\n",
       "<td>2.0191329</td>\n",
       "<td>0.2663022</td>\n",
       "<td>0.3562179</td>\n",
       "<td>0.1509350</td>\n",
       "<td>0.6057320</td>\n",
       "<td>50.9468320</td>\n",
       "<td>101.9132914</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000078</td>\n",
       "<td>0.1748262</td>\n",
       "<td>1.1938405</td>\n",
       "<td>1.8127897</td>\n",
       "<td>0.2106188</td>\n",
       "<td>0.3198145</td>\n",
       "<td>0.1193980</td>\n",
       "<td>0.7251300</td>\n",
       "<td>19.3840466</td>\n",
       "<td>81.2789663</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1365017</td>\n",
       "<td>0.8919586</td>\n",
       "<td>1.6286378</td>\n",
       "<td>0.1573604</td>\n",
       "<td>0.2873263</td>\n",
       "<td>0.0891889</td>\n",
       "<td>0.8143189</td>\n",
       "<td>-10.8041447</td>\n",
       "<td>62.8637822</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999922</td>\n",
       "<td>0.1058379</td>\n",
       "<td>0.6717355</td>\n",
       "<td>1.4691645</td>\n",
       "<td>0.1185084</td>\n",
       "<td>0.2591918</td>\n",
       "<td>0.0671683</td>\n",
       "<td>0.8814872</td>\n",
       "<td>-32.8264465</td>\n",
       "<td>46.9164486</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.7000039</td>\n",
       "<td>0.0851639</td>\n",
       "<td>0.4669144</td>\n",
       "<td>1.3259699</td>\n",
       "<td>0.0823736</td>\n",
       "<td>0.2339292</td>\n",
       "<td>0.0466969</td>\n",
       "<td>0.9281841</td>\n",
       "<td>-53.3085564</td>\n",
       "<td>32.5969935</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999961</td>\n",
       "<td>0.0716401</td>\n",
       "<td>0.3740471</td>\n",
       "<td>1.2069883</td>\n",
       "<td>0.0659898</td>\n",
       "<td>0.2129383</td>\n",
       "<td>0.0374018</td>\n",
       "<td>0.9655859</td>\n",
       "<td>-62.5952865</td>\n",
       "<td>20.6988296</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999883</td>\n",
       "<td>0.0578111</td>\n",
       "<td>0.2346094</td>\n",
       "<td>1.0989532</td>\n",
       "<td>0.0413901</td>\n",
       "<td>0.1938787</td>\n",
       "<td>0.0234591</td>\n",
       "<td>0.9890450</td>\n",
       "<td>-76.5390554</td>\n",
       "<td>9.8953233</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0055948</td>\n",
       "<td>0.1095368</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0193246</td>\n",
       "<td>0.1764212</td>\n",
       "<td>0.0109550</td>\n",
       "<td>1.0</td>\n",
       "<td>-89.0463201</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift      cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  --------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100148                   0.604922           4.15451   4.15451            0.732943         0.732943                    0.0416067       0.0416067                  315.451   315.451\n",
       "    2        0.0200102                   0.516132           3.14411   3.6498             0.554688         0.643902                    0.0314264       0.0730331                  214.411   264.98\n",
       "    3        0.0300055                   0.465732           2.97805   3.42603            0.525391         0.604424                    0.0297665       0.1028                     197.805   242.603\n",
       "    4        0.0400008                   0.434885           2.72342   3.25046            0.480469         0.57345                     0.0272214       0.130021                   172.342   225.046\n",
       "    5        0.0500156                   0.411749           2.32034   3.06422            0.409357         0.540593                    0.0232378       0.153259                   132.034   206.422\n",
       "    6        0.100012                    0.350375           2.27084   2.66761            0.400625         0.470623                    0.113533        0.266792                   127.084   166.761\n",
       "    7        0.150008                    0.306505           2.03402   2.45644            0.358844         0.433368                    0.101693        0.368485                   103.402   145.644\n",
       "    8        0.200004                    0.272813           1.72637   2.27394            0.304569         0.401171                    0.0863118       0.454797                   72.6371   127.394\n",
       "    9        0.299996                    0.22012            1.50947   2.01913            0.266302         0.356218                    0.150935        0.605732                   50.9468   101.913\n",
       "    10       0.400008                    0.174826           1.19384   1.81279            0.210619         0.319815                    0.119398        0.72513                    19.384    81.279\n",
       "    11       0.5                         0.136502           0.891959  1.62864            0.15736          0.287326                    0.0891889       0.814319                   -10.8041  62.8638\n",
       "    12       0.599992                    0.105838           0.671736  1.46916            0.118508         0.259192                    0.0671683       0.881487                   -32.8264  46.9164\n",
       "    13       0.700004                    0.0851639          0.466914  1.32597            0.0823736        0.233929                    0.0466969       0.928184                   -53.3086  32.597\n",
       "    14       0.799996                    0.0716401          0.374047  1.20699            0.0659898        0.212938                    0.0374018       0.965586                   -62.5953  20.6988\n",
       "    15       0.899988                    0.0578111          0.234609  1.09895            0.0413901        0.193879                    0.0234591       0.989045                   -76.5391  9.89532\n",
       "    16       1                           0.00559479         0.109537  1                  0.0193246        0.176421                    0.010955        1                          -89.0463  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Scoring History: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>timestamp</b></td>\n",
       "<td><b>duration</b></td>\n",
       "<td><b>number_of_trees</b></td>\n",
       "<td><b>training_rmse</b></td>\n",
       "<td><b>training_logloss</b></td>\n",
       "<td><b>training_auc</b></td>\n",
       "<td><b>training_lift</b></td>\n",
       "<td><b>training_classification_error</b></td>\n",
       "<td><b>validation_rmse</b></td>\n",
       "<td><b>validation_logloss</b></td>\n",
       "<td><b>validation_auc</b></td>\n",
       "<td><b>validation_lift</b></td>\n",
       "<td><b>validation_classification_error</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:20:53</td>\n",
       "<td> 0.507 sec</td>\n",
       "<td>0.0</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:21:09</td>\n",
       "<td>17.067 sec</td>\n",
       "<td>100.0</td>\n",
       "<td>0.3551600</td>\n",
       "<td>0.4028102</td>\n",
       "<td>0.7559429</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2773632</td>\n",
       "<td>0.3546847</td>\n",
       "<td>0.4013012</td>\n",
       "<td>0.7610853</td>\n",
       "<td>4.0550658</td>\n",
       "<td>0.2774871</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:21:36</td>\n",
       "<td>44.241 sec</td>\n",
       "<td>200.0</td>\n",
       "<td>0.3546097</td>\n",
       "<td>0.4016807</td>\n",
       "<td>0.7584293</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2738910</td>\n",
       "<td>0.3545292</td>\n",
       "<td>0.4009644</td>\n",
       "<td>0.7619967</td>\n",
       "<td>4.1103119</td>\n",
       "<td>0.2756520</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:22:15</td>\n",
       "<td> 1 min 23.477 sec</td>\n",
       "<td>300.0</td>\n",
       "<td>0.3544307</td>\n",
       "<td>0.4013222</td>\n",
       "<td>0.7592525</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2661518</td>\n",
       "<td>0.3544294</td>\n",
       "<td>0.4007347</td>\n",
       "<td>0.7625247</td>\n",
       "<td>4.1324104</td>\n",
       "<td>0.2806497</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:23:09</td>\n",
       "<td> 2 min 16.563 sec</td>\n",
       "<td>400.0</td>\n",
       "<td>0.3542955</td>\n",
       "<td>0.4010123</td>\n",
       "<td>0.7598601</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2741838</td>\n",
       "<td>0.3543655</td>\n",
       "<td>0.4005885</td>\n",
       "<td>0.7627619</td>\n",
       "<td>4.1434596</td>\n",
       "<td>0.2802593</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:24:16</td>\n",
       "<td> 3 min 23.899 sec</td>\n",
       "<td>500.0</td>\n",
       "<td>0.3542421</td>\n",
       "<td>0.4009071</td>\n",
       "<td>0.7600818</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2720336</td>\n",
       "<td>0.3543676</td>\n",
       "<td>0.4005762</td>\n",
       "<td>0.7628463</td>\n",
       "<td>4.1655581</td>\n",
       "<td>0.2790294</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:25:39</td>\n",
       "<td> 4 min 46.709 sec</td>\n",
       "<td>600.0</td>\n",
       "<td>0.3542157</td>\n",
       "<td>0.4008344</td>\n",
       "<td>0.7602705</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2614498</td>\n",
       "<td>0.3543582</td>\n",
       "<td>0.4005482</td>\n",
       "<td>0.7629427</td>\n",
       "<td>4.1876565</td>\n",
       "<td>0.2787756</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:27:18</td>\n",
       "<td> 6 min 25.601 sec</td>\n",
       "<td>700.0</td>\n",
       "<td>0.3541845</td>\n",
       "<td>0.4007659</td>\n",
       "<td>0.7604756</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2750205</td>\n",
       "<td>0.3543425</td>\n",
       "<td>0.4005276</td>\n",
       "<td>0.7630291</td>\n",
       "<td>4.1876565</td>\n",
       "<td>0.2822700</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:29:11</td>\n",
       "<td> 8 min 19.008 sec</td>\n",
       "<td>800.0</td>\n",
       "<td>0.3541727</td>\n",
       "<td>0.4007398</td>\n",
       "<td>0.7605263</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2686953</td>\n",
       "<td>0.3543511</td>\n",
       "<td>0.4005432</td>\n",
       "<td>0.7630018</td>\n",
       "<td>4.1545088</td>\n",
       "<td>0.2776628</td></tr></table></div>"
      ],
      "text/plain": [
       "    timestamp            duration          number_of_trees    training_rmse    training_logloss    training_auc    training_lift    training_classification_error    validation_rmse    validation_logloss    validation_auc    validation_lift    validation_classification_error\n",
       "--  -------------------  ----------------  -----------------  ---------------  ------------------  --------------  ---------------  -------------------------------  -----------------  --------------------  ----------------  -----------------  ---------------------------------\n",
       "    2017-07-12 22:20:53  0.507 sec         0                  nan              nan                 nan             nan              nan                              nan                nan                   nan               nan                nan\n",
       "    2017-07-12 22:21:09  17.067 sec        100                0.35516          0.40281             0.755943        5.68638          0.277363                         0.354685           0.401301              0.761085          4.05507            0.277487\n",
       "    2017-07-12 22:21:36  44.241 sec        200                0.35461          0.401681            0.758429        5.68638          0.273891                         0.354529           0.400964              0.761997          4.11031            0.275652\n",
       "    2017-07-12 22:22:15  1 min 23.477 sec  300                0.354431         0.401322            0.759252        5.68638          0.266152                         0.354429           0.400735              0.762525          4.13241            0.28065\n",
       "    2017-07-12 22:23:09  2 min 16.563 sec  400                0.354295         0.401012            0.75986         5.68638          0.274184                         0.354365           0.400589              0.762762          4.14346            0.280259\n",
       "    2017-07-12 22:24:16  3 min 23.899 sec  500                0.354242         0.400907            0.760082        5.68638          0.272034                         0.354368           0.400576              0.762846          4.16556            0.279029\n",
       "    2017-07-12 22:25:39  4 min 46.709 sec  600                0.354216         0.400834            0.76027         5.68638          0.26145                          0.354358           0.400548              0.762943          4.18766            0.278776\n",
       "    2017-07-12 22:27:18  6 min 25.601 sec  700                0.354185         0.400766            0.760476        5.68638          0.27502                          0.354343           0.400528              0.763029          4.18766            0.28227\n",
       "    2017-07-12 22:29:11  8 min 19.008 sec  800                0.354173         0.40074             0.760526        5.68638          0.268695                         0.354351           0.400543              0.763002          4.15451            0.277663"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable Importances: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>variable</b></td>\n",
       "<td><b>relative_importance</b></td>\n",
       "<td><b>scaled_importance</b></td>\n",
       "<td><b>percentage</b></td></tr>\n",
       "<tr><td>living_region</td>\n",
       "<td>515209.3125000</td>\n",
       "<td>1.0</td>\n",
       "<td>0.1952278</td></tr>\n",
       "<tr><td>tariff_id</td>\n",
       "<td>502785.1562500</td>\n",
       "<td>0.9758852</td>\n",
       "<td>0.1905199</td></tr>\n",
       "<tr><td>credit_sum</td>\n",
       "<td>219592.2187500</td>\n",
       "<td>0.4262194</td>\n",
       "<td>0.0832099</td></tr>\n",
       "<tr><td>credit_month</td>\n",
       "<td>199588.3593750</td>\n",
       "<td>0.3873928</td>\n",
       "<td>0.0756298</td></tr>\n",
       "<tr><td>age</td>\n",
       "<td>192851.4062500</td>\n",
       "<td>0.3743166</td>\n",
       "<td>0.0730770</td></tr>\n",
       "<tr><td>score_shk</td>\n",
       "<td>181426.1875000</td>\n",
       "<td>0.3521407</td>\n",
       "<td>0.0687477</td></tr>\n",
       "<tr><td>job_position</td>\n",
       "<td>149373.0937500</td>\n",
       "<td>0.2899270</td>\n",
       "<td>0.0566018</td></tr>\n",
       "<tr><td>credit_count</td>\n",
       "<td>126724.2968750</td>\n",
       "<td>0.2459666</td>\n",
       "<td>0.0480195</td></tr>\n",
       "<tr><td>overdue_credit_count</td>\n",
       "<td>112300.5390625</td>\n",
       "<td>0.2179707</td>\n",
       "<td>0.0425539</td></tr>\n",
       "<tr><td>education</td>\n",
       "<td>90957.6406250</td>\n",
       "<td>0.1765450</td>\n",
       "<td>0.0344665</td></tr>\n",
       "<tr><td>okrug</td>\n",
       "<td>88394.7890625</td>\n",
       "<td>0.1715706</td>\n",
       "<td>0.0334954</td></tr>\n",
       "<tr><td>marital_status</td>\n",
       "<td>80072.0546875</td>\n",
       "<td>0.1554166</td>\n",
       "<td>0.0303416</td></tr>\n",
       "<tr><td>monthly_income</td>\n",
       "<td>78311.375</td>\n",
       "<td>0.1519991</td>\n",
       "<td>0.0296745</td></tr>\n",
       "<tr><td>avregzarplata</td>\n",
       "<td>60994.9648438</td>\n",
       "<td>0.1183887</td>\n",
       "<td>0.0231128</td></tr>\n",
       "<tr><td>gender</td>\n",
       "<td>40435.0156250</td>\n",
       "<td>0.0784827</td>\n",
       "<td>0.0153220</td></tr></table></div>"
      ],
      "text/plain": [
       "variable              relative_importance    scaled_importance    percentage\n",
       "--------------------  ---------------------  -------------------  ------------\n",
       "living_region         515209                 1                    0.195228\n",
       "tariff_id             502785                 0.975885             0.19052\n",
       "credit_sum            219592                 0.426219             0.0832099\n",
       "credit_month          199588                 0.387393             0.0756298\n",
       "age                   192851                 0.374317             0.073077\n",
       "score_shk             181426                 0.352141             0.0687477\n",
       "job_position          149373                 0.289927             0.0566018\n",
       "credit_count          126724                 0.245967             0.0480195\n",
       "overdue_credit_count  112301                 0.217971             0.0425539\n",
       "education             90957.6                0.176545             0.0344665\n",
       "okrug                 88394.8                0.171571             0.0334954\n",
       "marital_status        80072.1                0.155417             0.0303416\n",
       "monthly_income        78311.4                0.151999             0.0296745\n",
       "avregzarplata         60995                  0.118389             0.0231128\n",
       "gender                40435                  0.0784827            0.015322"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "savedmodel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parse progress: |█████████████████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "newobservations = h2o.H2OFrame(newdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rows:91940\n",
      "Cols:15\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>       </th><th>gender            </th><th>age               </th><th>marital_status    </th><th>job_position      </th><th>credit_sum        </th><th>credit_month      </th><th>score_shk          </th><th>education         </th><th>tariff_id         </th><th>living_region     </th><th>okrug            </th><th>avregzarplata    </th><th>monthly_income    </th><th>credit_count      </th><th>overdue_credit_count  </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td>type   </td><td>int               </td><td>int               </td><td>int               </td><td>int               </td><td>real              </td><td>int               </td><td>real               </td><td>int               </td><td>int               </td><td>int               </td><td>int              </td><td>int              </td><td>int               </td><td>int               </td><td>int                   </td></tr>\n",
       "<tr><td>mins   </td><td>1.0               </td><td>18.0              </td><td>1.0               </td><td>1.0               </td><td>3000.0            </td><td>3.0               </td><td>0.0                </td><td>1.0               </td><td>1.0               </td><td>1.0               </td><td>1.0              </td><td>-1.0             </td><td>0.0               </td><td>-1.0              </td><td>-1.0                  </td></tr>\n",
       "<tr><td>mean   </td><td>1.4712747443985348</td><td>36.46124646508572 </td><td>3.200250163149864 </td><td>13.207211224711791</td><td>26068.179130411067</td><td>10.981335653687253</td><td>0.46926984104850983</td><td>3.2030237111159527</td><td>14.04566021318252 </td><td>43.117478790515435</td><td>4.92212312377639 </td><td>32906.87028496852</td><td>40083.18676310629 </td><td>1.9490211007178506</td><td>-0.007635414400696094 </td></tr>\n",
       "<tr><td>maxs   </td><td>2.0               </td><td>71.0              </td><td>5.0               </td><td>99.0              </td><td>200000.0          </td><td>36.0              </td><td>1.255892           </td><td>5.0               </td><td>99.0              </td><td>99.0              </td><td>99.0             </td><td>66880.0          </td><td>700000.0          </td><td>22.0              </td><td>3.0                   </td></tr>\n",
       "<tr><td>sigma  </td><td>0.4991768924038961</td><td>10.512199852637746</td><td>0.7438585295494443</td><td>3.1795715276335166</td><td>16228.023980509111</td><td>3.5515480321670436</td><td>0.12461549423496118</td><td>1.0606857283369242</td><td>11.622128361707299</td><td>22.24019185524421 </td><td>3.916334243844334</td><td>12598.09197702788</td><td>24652.556394595205</td><td>1.8555032082047822</td><td>0.3087924668758704    </td></tr>\n",
       "<tr><td>zeros  </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>5                  </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                </td><td>0                </td><td>1                 </td><td>13682             </td><td>83267                 </td></tr>\n",
       "<tr><td>missing</td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                  </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                </td><td>0                </td><td>0                 </td><td>0                 </td><td>0                     </td></tr>\n",
       "<tr><td>0      </td><td>2.0               </td><td>48.0              </td><td>1.0               </td><td>14.0              </td><td>16558.0           </td><td>10.0              </td><td>0.370409           </td><td>4.0               </td><td>2.0               </td><td>23.0              </td><td>8.0              </td><td>25850.0          </td><td>34000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>1      </td><td>2.0               </td><td>29.0              </td><td>3.0               </td><td>14.0              </td><td>7028.72           </td><td>6.0               </td><td>0.377281           </td><td>4.0               </td><td>2.0               </td><td>30.0              </td><td>7.0              </td><td>66880.0          </td><td>19000.0           </td><td>3.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>2      </td><td>1.0               </td><td>20.0              </td><td>2.0               </td><td>14.0              </td><td>13019.0           </td><td>10.0              </td><td>0.538515           </td><td>2.0               </td><td>2.0               </td><td>64.0              </td><td>2.0              </td><td>23430.0          </td><td>25000.0           </td><td>1.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>3      </td><td>2.0               </td><td>41.0              </td><td>4.0               </td><td>8.0               </td><td>9379.0            </td><td>10.0              </td><td>0.48252            </td><td>4.0               </td><td>28.0              </td><td>8.0               </td><td>8.0              </td><td>23650.0          </td><td>30000.0           </td><td>0.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>4      </td><td>2.0               </td><td>34.0              </td><td>4.0               </td><td>14.0              </td><td>13990.0           </td><td>6.0               </td><td>0.48591399999999996</td><td>2.0               </td><td>28.0              </td><td>77.0              </td><td>6.0              </td><td>26620.0          </td><td>20000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>5      </td><td>2.0               </td><td>37.0              </td><td>3.0               </td><td>14.0              </td><td>21141.0           </td><td>12.0              </td><td>0.795377           </td><td>4.0               </td><td>2.0               </td><td>68.0              </td><td>4.0              </td><td>22000.0          </td><td>40000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>6      </td><td>1.0               </td><td>38.0              </td><td>3.0               </td><td>14.0              </td><td>38647.0           </td><td>10.0              </td><td>0.35403999999999997</td><td>2.0               </td><td>2.0               </td><td>33.0              </td><td>2.0              </td><td>26840.0          </td><td>35000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>7      </td><td>2.0               </td><td>57.0              </td><td>3.0               </td><td>14.0              </td><td>33457.0           </td><td>10.0              </td><td>0.46115799999999996</td><td>2.0               </td><td>2.0               </td><td>31.0              </td><td>7.0              </td><td>42460.0          </td><td>24000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>8      </td><td>1.0               </td><td>45.0              </td><td>4.0               </td><td>14.0              </td><td>16339.0           </td><td>12.0              </td><td>0.47612            </td><td>4.0               </td><td>2.0               </td><td>73.0              </td><td>6.0              </td><td>56000.0          </td><td>55000.0           </td><td>7.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>9      </td><td>1.0               </td><td>26.0              </td><td>3.0               </td><td>14.0              </td><td>16919.0           </td><td>10.0              </td><td>0.570206           </td><td>2.0               </td><td>28.0              </td><td>68.0              </td><td>4.0              </td><td>22000.0          </td><td>20000.0           </td><td>1.0               </td><td>0.0                   </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "newobservations.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "newobservations['gender'] = newobservations['gender'].asfactor()\n",
    "newobservations['marital_status'] = newobservations['marital_status'].asfactor()\n",
    "newobservations['job_position'] = newobservations['job_position'].asfactor()\n",
    "newobservations['education'] = newobservations['education'].asfactor()\n",
    "newobservations['tariff_id'] = newobservations['tariff_id'].asfactor()\n",
    "newobservations['living_region'] = newobservations['living_region'].asfactor()\n",
    "newobservations['okrug'] = newobservations['okrug'].asfactor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rows:91940\n",
      "Cols:15\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>       </th><th>gender  </th><th>age               </th><th>marital_status  </th><th>job_position  </th><th>credit_sum        </th><th>credit_month      </th><th>score_shk          </th><th>education  </th><th>tariff_id  </th><th>living_region  </th><th>okrug  </th><th>avregzarplata    </th><th>monthly_income    </th><th>credit_count      </th><th>overdue_credit_count  </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td>type   </td><td>enum    </td><td>int               </td><td>enum            </td><td>enum          </td><td>real              </td><td>int               </td><td>real               </td><td>enum       </td><td>enum       </td><td>enum           </td><td>enum   </td><td>int              </td><td>int               </td><td>int               </td><td>int                   </td></tr>\n",
       "<tr><td>mins   </td><td>        </td><td>18.0              </td><td>                </td><td>              </td><td>3000.0            </td><td>3.0               </td><td>0.0                </td><td>           </td><td>           </td><td>               </td><td>       </td><td>-1.0             </td><td>0.0               </td><td>-1.0              </td><td>-1.0                  </td></tr>\n",
       "<tr><td>mean   </td><td>        </td><td>36.46124646508572 </td><td>                </td><td>              </td><td>26068.179130411067</td><td>10.981335653687253</td><td>0.46926984104850983</td><td>           </td><td>           </td><td>               </td><td>       </td><td>32906.87028496852</td><td>40083.18676310629 </td><td>1.9490211007178506</td><td>-0.007635414400696094 </td></tr>\n",
       "<tr><td>maxs   </td><td>        </td><td>71.0              </td><td>                </td><td>              </td><td>200000.0          </td><td>36.0              </td><td>1.255892           </td><td>           </td><td>           </td><td>               </td><td>       </td><td>66880.0          </td><td>700000.0          </td><td>22.0              </td><td>3.0                   </td></tr>\n",
       "<tr><td>sigma  </td><td>        </td><td>10.512199852637746</td><td>                </td><td>              </td><td>16228.023980509111</td><td>3.5515480321670436</td><td>0.12461549423496118</td><td>           </td><td>           </td><td>               </td><td>       </td><td>12598.09197702788</td><td>24652.556394595205</td><td>1.8555032082047822</td><td>0.3087924668758704    </td></tr>\n",
       "<tr><td>zeros  </td><td>        </td><td>0                 </td><td>                </td><td>              </td><td>0                 </td><td>0                 </td><td>5                  </td><td>           </td><td>           </td><td>               </td><td>       </td><td>0                </td><td>1                 </td><td>13682             </td><td>83267                 </td></tr>\n",
       "<tr><td>missing</td><td>0       </td><td>0                 </td><td>0               </td><td>0             </td><td>0                 </td><td>0                 </td><td>0                  </td><td>0          </td><td>0          </td><td>0              </td><td>0      </td><td>0                </td><td>0                 </td><td>0                 </td><td>0                     </td></tr>\n",
       "<tr><td>0      </td><td>2       </td><td>48.0              </td><td>1               </td><td>14            </td><td>16558.0           </td><td>10.0              </td><td>0.370409           </td><td>4          </td><td>2          </td><td>23             </td><td>8      </td><td>25850.0          </td><td>34000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>1      </td><td>2       </td><td>29.0              </td><td>3               </td><td>14            </td><td>7028.72           </td><td>6.0               </td><td>0.377281           </td><td>4          </td><td>2          </td><td>30             </td><td>7      </td><td>66880.0          </td><td>19000.0           </td><td>3.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>2      </td><td>1       </td><td>20.0              </td><td>2               </td><td>14            </td><td>13019.0           </td><td>10.0              </td><td>0.538515           </td><td>2          </td><td>2          </td><td>64             </td><td>2      </td><td>23430.0          </td><td>25000.0           </td><td>1.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>3      </td><td>2       </td><td>41.0              </td><td>4               </td><td>8             </td><td>9379.0            </td><td>10.0              </td><td>0.48252            </td><td>4          </td><td>28         </td><td>8              </td><td>8      </td><td>23650.0          </td><td>30000.0           </td><td>0.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>4      </td><td>2       </td><td>34.0              </td><td>4               </td><td>14            </td><td>13990.0           </td><td>6.0               </td><td>0.48591399999999996</td><td>2          </td><td>28         </td><td>77             </td><td>6      </td><td>26620.0          </td><td>20000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>5      </td><td>2       </td><td>37.0              </td><td>3               </td><td>14            </td><td>21141.0           </td><td>12.0              </td><td>0.795377           </td><td>4          </td><td>2          </td><td>68             </td><td>4      </td><td>22000.0          </td><td>40000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>6      </td><td>1       </td><td>38.0              </td><td>3               </td><td>14            </td><td>38647.0           </td><td>10.0              </td><td>0.35403999999999997</td><td>2          </td><td>2          </td><td>33             </td><td>2      </td><td>26840.0          </td><td>35000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>7      </td><td>2       </td><td>57.0              </td><td>3               </td><td>14            </td><td>33457.0           </td><td>10.0              </td><td>0.46115799999999996</td><td>2          </td><td>2          </td><td>31             </td><td>7      </td><td>42460.0          </td><td>24000.0           </td><td>2.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>8      </td><td>1       </td><td>45.0              </td><td>4               </td><td>14            </td><td>16339.0           </td><td>12.0              </td><td>0.47612            </td><td>4          </td><td>2          </td><td>73             </td><td>6      </td><td>56000.0          </td><td>55000.0           </td><td>7.0               </td><td>0.0                   </td></tr>\n",
       "<tr><td>9      </td><td>1       </td><td>26.0              </td><td>3               </td><td>14            </td><td>16919.0           </td><td>10.0              </td><td>0.570206           </td><td>2          </td><td>28         </td><td>68             </td><td>4      </td><td>22000.0          </td><td>20000.0           </td><td>1.0               </td><td>0.0                   </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "newobservations.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "drf prediction progress: |████████████████████████████████████████████████| 100%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th style=\"text-align: right;\">  predict</th><th style=\"text-align: right;\">      p0</th><th style=\"text-align: right;\">       p1</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.881424</td><td style=\"text-align: right;\">0.118576 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        1</td><td style=\"text-align: right;\">0.665973</td><td style=\"text-align: right;\">0.334027 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.813923</td><td style=\"text-align: right;\">0.186077 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        1</td><td style=\"text-align: right;\">0.659044</td><td style=\"text-align: right;\">0.340956 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.89968 </td><td style=\"text-align: right;\">0.10032  </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        1</td><td style=\"text-align: right;\">0.660642</td><td style=\"text-align: right;\">0.339358 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.936356</td><td style=\"text-align: right;\">0.0636438</td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.921076</td><td style=\"text-align: right;\">0.078924 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        1</td><td style=\"text-align: right;\">0.723928</td><td style=\"text-align: right;\">0.276072 </td></tr>\n",
       "<tr><td style=\"text-align: right;\">        0</td><td style=\"text-align: right;\">0.960352</td><td style=\"text-align: right;\">0.0396476</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred = savedmodel.predict(newobservations)\n",
    "pred"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Улучшение качества моделей классов RandomForestClassifier и H2ORandomForestEstimator с помощью конструирования новых признаков"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "train['tariff']=train['tariff_id'].astype('int')\n",
    "test['tariff']=test['tariff_id'].astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train['dummy_paym'] = train['credit_sum'] / train['credit_month']\n",
    "train['dummy_pti'] = train['dummy_paym'] / train['monthly_income']\n",
    "train['dummy_pti'][train['dummy_pti'] == np.inf] = 1\n",
    "\n",
    "for i in ['dummy_paym', 'dummy_pti']:\n",
    "    if i in train.columns:\n",
    "        train[i].fillna(-1, inplace = True)\n",
    "\n",
    "test['dummy_paym'] = test['credit_sum'] / test['credit_month']\n",
    "test['dummy_pti'] = test['dummy_paym'] / test['monthly_income']\n",
    "test['dummy_pti'][test['dummy_pti'] == np.inf] = 1\n",
    "\n",
    "for i in ['dummy_paym', 'dummy_pti']:\n",
    "    if i in test.columns:\n",
    "        test[i].fillna(-1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.drop(['avregzarplata', 'okrug'], axis=1, inplace=True)\n",
    "test.drop(['avregzarplata', 'okrug'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train['tariff_sq'] = train['tariff']**2\n",
    "test['tariff_sq'] = test['tariff']**2\n",
    "\n",
    "train['age_sq'] = train['age']**2\n",
    "test['age_sq'] = test['age']**2\n",
    "\n",
    "train['credit_sum_sq'] = train['credit_sum']**2\n",
    "test['credit_sum_sq'] = test['credit_sum']**2\n",
    "\n",
    "train['score_sq'] = train['score_shk']**2\n",
    "test['score_sq'] = test['score_shk']**2\n",
    "\n",
    "train['income_sq'] = train['monthly_income']**2\n",
    "test['income_sq'] = test['monthly_income']**2\n",
    "\n",
    "train['credit_month_sq'] = train['credit_month']**2\n",
    "test['credit_month_sq'] = test['credit_month']**2\n",
    "\n",
    "train['credit_count_sq'] = train['credit_count']**2\n",
    "test['credit_count_sq'] = test['credit_count']**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Переменные после get_dummies:\n",
      " ['age', 'credit_sum', 'credit_month', 'score_shk', 'monthly_income', 'credit_count', 'overdue_credit_count', 'tariff', 'dummy_paym', 'dummy_pti', 'tariff_sq', 'age_sq', 'credit_sum_sq', 'score_sq', 'income_sq', 'credit_month_sq', 'credit_count_sq', 'gender_1', 'gender_2', 'marital_status_1.0', 'marital_status_2.0', 'marital_status_3.0', 'marital_status_4.0', 'marital_status_5.0', 'job_position_1', 'job_position_10', 'job_position_11', 'job_position_13', 'job_position_14', 'job_position_15', 'job_position_16', 'job_position_17', 'job_position_18', 'job_position_2', 'job_position_3', 'job_position_4', 'job_position_6', 'job_position_8', 'job_position_99', 'education_1.0', 'education_2.0', 'education_3.0', 'education_4.0', 'education_5.0', 'tariff_id_1', 'tariff_id_10', 'tariff_id_11', 'tariff_id_12', 'tariff_id_13', 'tariff_id_18', 'tariff_id_19', 'tariff_id_2', 'tariff_id_20', 'tariff_id_21', 'tariff_id_22', 'tariff_id_23', 'tariff_id_25', 'tariff_id_28', 'tariff_id_29', 'tariff_id_3', 'tariff_id_30', 'tariff_id_31', 'tariff_id_32', 'tariff_id_4', 'tariff_id_5', 'tariff_id_6', 'tariff_id_7', 'tariff_id_8', 'tariff_id_9', 'tariff_id_99', 'living_region_1.0', 'living_region_10.0', 'living_region_11.0', 'living_region_12.0', 'living_region_13.0', 'living_region_14.0', 'living_region_15.0', 'living_region_16.0', 'living_region_17.0', 'living_region_18.0', 'living_region_19.0', 'living_region_2.0', 'living_region_20.0', 'living_region_21.0', 'living_region_22.0', 'living_region_23.0', 'living_region_24.0', 'living_region_25.0', 'living_region_26.0', 'living_region_27.0', 'living_region_28.0', 'living_region_29.0', 'living_region_3.0', 'living_region_30.0', 'living_region_31.0', 'living_region_32.0', 'living_region_33.0', 'living_region_34.0', 'living_region_35.0', 'living_region_36.0', 'living_region_37.0', 'living_region_38.0', 'living_region_39.0', 'living_region_4.0', 'living_region_40.0', 'living_region_41.0', 'living_region_43.0', 'living_region_44.0', 'living_region_45.0', 'living_region_46.0', 'living_region_47.0', 'living_region_48.0', 'living_region_49.0', 'living_region_5.0', 'living_region_50.0', 'living_region_51.0', 'living_region_52.0', 'living_region_53.0', 'living_region_54.0', 'living_region_55.0', 'living_region_56.0', 'living_region_57.0', 'living_region_58.0', 'living_region_59.0', 'living_region_6.0', 'living_region_60.0', 'living_region_61.0', 'living_region_62.0', 'living_region_63.0', 'living_region_64.0', 'living_region_65.0', 'living_region_66.0', 'living_region_67.0', 'living_region_68.0', 'living_region_69.0', 'living_region_7.0', 'living_region_70.0', 'living_region_71.0', 'living_region_72.0', 'living_region_73.0', 'living_region_74.0', 'living_region_75.0', 'living_region_76.0', 'living_region_77.0', 'living_region_78.0', 'living_region_79.0', 'living_region_8.0', 'living_region_80.0', 'living_region_81.0', 'living_region_82.0', 'living_region_9.0', 'living_region_99']\n",
      "Переменные после get_dummies:\n",
      " ['age', 'credit_sum', 'credit_month', 'score_shk', 'monthly_income', 'credit_count', 'overdue_credit_count', 'tariff', 'dummy_paym', 'dummy_pti', 'tariff_sq', 'age_sq', 'credit_sum_sq', 'score_sq', 'income_sq', 'credit_month_sq', 'credit_count_sq', 'gender_1', 'gender_2', 'marital_status_1.0', 'marital_status_2.0', 'marital_status_3.0', 'marital_status_4.0', 'marital_status_5.0', 'job_position_1', 'job_position_10', 'job_position_11', 'job_position_13', 'job_position_14', 'job_position_15', 'job_position_16', 'job_position_17', 'job_position_18', 'job_position_2', 'job_position_3', 'job_position_4', 'job_position_6', 'job_position_8', 'job_position_99', 'education_1.0', 'education_2.0', 'education_3.0', 'education_4.0', 'education_5.0', 'tariff_id_1', 'tariff_id_10', 'tariff_id_11', 'tariff_id_12', 'tariff_id_13', 'tariff_id_18', 'tariff_id_19', 'tariff_id_2', 'tariff_id_20', 'tariff_id_21', 'tariff_id_22', 'tariff_id_23', 'tariff_id_25', 'tariff_id_28', 'tariff_id_29', 'tariff_id_3', 'tariff_id_30', 'tariff_id_31', 'tariff_id_32', 'tariff_id_4', 'tariff_id_5', 'tariff_id_6', 'tariff_id_7', 'tariff_id_8', 'tariff_id_9', 'tariff_id_99', 'living_region_1.0', 'living_region_10.0', 'living_region_11.0', 'living_region_12.0', 'living_region_13.0', 'living_region_14.0', 'living_region_15.0', 'living_region_16.0', 'living_region_17.0', 'living_region_18.0', 'living_region_19.0', 'living_region_2.0', 'living_region_20.0', 'living_region_21.0', 'living_region_22.0', 'living_region_23.0', 'living_region_24.0', 'living_region_25.0', 'living_region_26.0', 'living_region_27.0', 'living_region_28.0', 'living_region_29.0', 'living_region_3.0', 'living_region_30.0', 'living_region_31.0', 'living_region_32.0', 'living_region_33.0', 'living_region_34.0', 'living_region_35.0', 'living_region_36.0', 'living_region_37.0', 'living_region_38.0', 'living_region_39.0', 'living_region_4.0', 'living_region_40.0', 'living_region_41.0', 'living_region_43.0', 'living_region_44.0', 'living_region_45.0', 'living_region_46.0', 'living_region_47.0', 'living_region_48.0', 'living_region_49.0', 'living_region_5.0', 'living_region_50.0', 'living_region_51.0', 'living_region_52.0', 'living_region_53.0', 'living_region_54.0', 'living_region_55.0', 'living_region_56.0', 'living_region_57.0', 'living_region_58.0', 'living_region_59.0', 'living_region_6.0', 'living_region_60.0', 'living_region_61.0', 'living_region_62.0', 'living_region_63.0', 'living_region_64.0', 'living_region_65.0', 'living_region_66.0', 'living_region_67.0', 'living_region_68.0', 'living_region_69.0', 'living_region_7.0', 'living_region_70.0', 'living_region_71.0', 'living_region_72.0', 'living_region_73.0', 'living_region_74.0', 'living_region_75.0', 'living_region_76.0', 'living_region_77.0', 'living_region_78.0', 'living_region_79.0', 'living_region_8.0', 'living_region_80.0', 'living_region_81.0', 'living_region_82.0', 'living_region_9.0', 'living_region_99']\n"
     ]
    }
   ],
   "source": [
    "train_dummies = pd.get_dummies(train)\n",
    "test_dummies = pd.get_dummies(test)\n",
    "\n",
    "y_train = train_dummies.loc[:, 'open_account_flg_1']\n",
    "y_test = test_dummies.loc[:, 'open_account_flg_1']\n",
    "X_train = train_dummies.loc[:, 'age':'living_region_99']\n",
    "X_test = test_dummies.loc[:, 'age':'living_region_99']\n",
    "\n",
    "print(\"Переменные после get_dummies:\\n\", list(X_train.columns))\n",
    "print(\"Переменные после get_dummies:\\n\", list(X_test.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC на обучающей выборке: 1.000\n",
      "AUC на контрольной выборке: 0.755\n"
     ]
    }
   ],
   "source": [
    "forest4=RandomForestClassifier(n_estimators=800, random_state=152, n_jobs=-1)\n",
    "forest4.fit(X_train, y_train)\n",
    "print(\"AUC на обучающей выборке: {:.3f}\".format(roc_auc_score(y_train, \n",
    "forest4.predict_proba(X_train)[:, 1])))\n",
    "print(\"AUC на контрольной выборке: {:.3f}\".format(roc_auc_score(y_test, \n",
    "forest4.predict_proba(X_test)[:, 1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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47JNFNtXVDFPQWD2ryhfeFrjwtn7sY/9V4tZ7TLc0PQcBmTX8ahpPIPA1c7LI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oAAAg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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cd1d1f39e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_ensemble(forest4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC на обучающей выборке: 0.895\n",
      "AUC на контрольной выборке: 0.766\n"
     ]
    }
   ],
   "source": [
    "forest5=RandomForestClassifier(n_estimators=800, max_depth=17, random_state=152, n_jobs=-1)\n",
    "forest5.fit(X_train, y_train)\n",
    "print(\"AUC на обучающей выборке: {:.3f}\".format(roc_auc_score(y_train, \n",
    "forest5.predict_proba(X_train)[:, 1])))\n",
    "print(\"AUC на контрольной выборке: {:.3f}\".format(roc_auc_score(y_test, \n",
    "forest5.predict_proba(X_test)[:, 1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parse progress: |█████████████████████████████████████████████████████████| 100%\n",
      "Parse progress: |█████████████████████████████████████████████████████████| 100%\n",
      "Rows:119522\n",
      "Cols:24\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>       </th><th>gender  </th><th>age               </th><th>marital_status  </th><th>job_position  </th><th>credit_sum        </th><th>credit_month      </th><th>score_shk          </th><th>education  </th><th>tariff_id  </th><th>living_region  </th><th>monthly_income    </th><th>credit_count      </th><th>overdue_credit_count  </th><th>open_account_flg  </th><th>tariff            </th><th>dummy_paym        </th><th>dummy_pti            </th><th>tariff_sq         </th><th>age_sq           </th><th>credit_sum_sq     </th><th>score_sq           </th><th>income_sq        </th><th>credit_month_sq   </th><th>credit_count_sq   </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td>type   </td><td>enum    </td><td>int               </td><td>enum            </td><td>enum          </td><td>real              </td><td>int               </td><td>real               </td><td>enum       </td><td>enum       </td><td>enum           </td><td>int               </td><td>int               </td><td>int                   </td><td>enum              </td><td>int               </td><td>real              </td><td>real                 </td><td>int               </td><td>int              </td><td>real              </td><td>real               </td><td>int              </td><td>int               </td><td>int               </td></tr>\n",
       "<tr><td>mins   </td><td>        </td><td>18.0              </td><td>                </td><td>              </td><td>2736.0            </td><td>3.0               </td><td>0.0                </td><td>           </td><td>           </td><td>               </td><td>5000.0            </td><td>-1.0              </td><td>-1.0                  </td><td>                  </td><td>1.0               </td><td>104.66666666666669</td><td>0.0009777777777777775</td><td>1.0               </td><td>324.0            </td><td>7485696.0         </td><td>0.0                </td><td>25000000.0       </td><td>9.0               </td><td>0.0               </td></tr>\n",
       "<tr><td>mean   </td><td>        </td><td>36.47966901490939 </td><td>                </td><td>              </td><td>26084.89449298038 </td><td>10.976665383778704</td><td>0.46972772229380466</td><td>           </td><td>           </td><td>               </td><td>40108.718662672894</td><td>1.9372416793561038</td><td>-0.011094191864259298 </td><td>                  </td><td>14.161593681497958</td><td>2463.2615781578575</td><td>0.07040265223232711  </td><td>335.31083817205285</td><td>1442.117158347415</td><td>943825322.056857  </td><td>0.23605992004028942</td><td>2236524121.859719</td><td>132.8577751376316 </td><td>7.244114054316355 </td></tr>\n",
       "<tr><td>maxs   </td><td>        </td><td>71.0              </td><td>                </td><td>              </td><td>200000.0          </td><td>36.0              </td><td>1.128291           </td><td>           </td><td>           </td><td>               </td><td>900000.0          </td><td>21.0              </td><td>3.0                   </td><td>                  </td><td>99.0              </td><td>39966.666666666664</td><td>1.998333333333333    </td><td>9801.0            </td><td>5041.0           </td><td>40000000000.0     </td><td>1.273040580681     </td><td>810000000000.0   </td><td>1296.0            </td><td>441.0             </td></tr>\n",
       "<tr><td>sigma  </td><td>        </td><td>10.552338060975371</td><td>                </td><td>              </td><td>16229.781427175623</td><td>3.5171999789032435</td><td>0.12416084700379575</td><td>           </td><td>           </td><td>               </td><td>25056.337758251673</td><td>1.8684854669182152</td><td>0.31294568174117815   </td><td>                  </td><td>11.608670469682282</td><td>1566.1684461638217</td><td>0.04345641333768785  </td><td>364.66979869323853</td><td>861.368746602237 </td><td>1301945308.5465603</td><td>0.12199803707621279</td><td>7059444131.993064</td><td>114.75763296620572</td><td>12.907619541010915</td></tr>\n",
       "<tr><td>zeros  </td><td>        </td><td>0                 </td><td>                </td><td>              </td><td>0                 </td><td>0                 </td><td>1                  </td><td>           </td><td>           </td><td>               </td><td>0                 </td><td>18134             </td><td>107935                </td><td>                  </td><td>0                 </td><td>0                 </td><td>0                    </td><td>0                 </td><td>0                </td><td>0                 </td><td>1                  </td><td>0                </td><td>0                 </td><td>18134             </td></tr>\n",
       "<tr><td>missing</td><td>0       </td><td>0                 </td><td>0               </td><td>0             </td><td>0                 </td><td>0                 </td><td>0                  </td><td>0          </td><td>0          </td><td>0              </td><td>0                 </td><td>0                 </td><td>0                     </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                    </td><td>0                 </td><td>0                </td><td>0                 </td><td>0                  </td><td>0                </td><td>0                 </td><td>0                 </td></tr>\n",
       "<tr><td>0      </td><td>2       </td><td>28.0              </td><td>4               </td><td>14            </td><td>33579.0           </td><td>10.0              </td><td>0.43135999999999997</td><td>4          </td><td>20         </td><td>2              </td><td>36000.0           </td><td>2.0               </td><td>0.0                   </td><td>0                 </td><td>20.0              </td><td>3357.9            </td><td>0.093275             </td><td>400.0             </td><td>784.0            </td><td>1127549241.0      </td><td>0.18607144960000002</td><td>1296000000.0     </td><td>100.0             </td><td>4.0               </td></tr>\n",
       "<tr><td>1      </td><td>2       </td><td>38.0              </td><td>4               </td><td>14            </td><td>23511.0           </td><td>10.0              </td><td>0.35847199999999996</td><td>2          </td><td>19         </td><td>68             </td><td>45000.0           </td><td>2.0               </td><td>0.0                   </td><td>0                 </td><td>19.0              </td><td>2351.1            </td><td>0.05224666666666667  </td><td>361.0             </td><td>1444.0           </td><td>552767121.0       </td><td>0.128502174784     </td><td>2025000000.0     </td><td>100.0             </td><td>4.0               </td></tr>\n",
       "<tr><td>2      </td><td>1       </td><td>25.0              </td><td>3               </td><td>14            </td><td>39990.0           </td><td>24.0              </td><td>0.613475           </td><td>2          </td><td>25         </td><td>60             </td><td>50000.0           </td><td>6.0               </td><td>0.0                   </td><td>0                 </td><td>25.0              </td><td>1666.25           </td><td>0.033325             </td><td>625.0             </td><td>625.0            </td><td>1599200100.0      </td><td>0.376351575625     </td><td>2500000000.0     </td><td>576.0             </td><td>36.0              </td></tr>\n",
       "<tr><td>3      </td><td>1       </td><td>65.0              </td><td>4               </td><td>15            </td><td>3490.0            </td><td>6.0               </td><td>0.371355           </td><td>2          </td><td>18         </td><td>59             </td><td>35000.0           </td><td>4.0               </td><td>0.0                   </td><td>0                 </td><td>18.0              </td><td>581.6666666666666 </td><td>0.016619047619047617 </td><td>324.0             </td><td>4225.0           </td><td>12180100.0        </td><td>0.137904536025     </td><td>1225000000.0     </td><td>36.0              </td><td>16.0              </td></tr>\n",
       "<tr><td>4      </td><td>2       </td><td>49.0              </td><td>3               </td><td>2             </td><td>36358.0           </td><td>10.0              </td><td>0.645187           </td><td>4          </td><td>28         </td><td>77             </td><td>50000.0           </td><td>2.0               </td><td>0.0                   </td><td>0                 </td><td>28.0              </td><td>3635.8            </td><td>0.072716             </td><td>784.0             </td><td>2401.0           </td><td>1321904164.0      </td><td>0.41626626496899993</td><td>2500000000.0     </td><td>100.0             </td><td>4.0               </td></tr>\n",
       "<tr><td>5      </td><td>1       </td><td>39.0              </td><td>4               </td><td>14            </td><td>13209.0           </td><td>10.0              </td><td>0.45511999999999997</td><td>4          </td><td>2          </td><td>55             </td><td>60000.0           </td><td>1.0               </td><td>0.0                   </td><td>0                 </td><td>2.0               </td><td>1320.9            </td><td>0.022015             </td><td>4.0               </td><td>1521.0           </td><td>174477681.0       </td><td>0.20713421440000002</td><td>3600000000.0     </td><td>100.0             </td><td>1.0               </td></tr>\n",
       "<tr><td>6      </td><td>2       </td><td>30.0              </td><td>4               </td><td>14            </td><td>15192.050000000001</td><td>12.0              </td><td>0.451993           </td><td>4          </td><td>2          </td><td>57             </td><td>25000.0           </td><td>1.0               </td><td>0.0                   </td><td>0                 </td><td>2.0               </td><td>1266.0041666666666</td><td>0.050640166666666674 </td><td>4.0               </td><td>900.0            </td><td>230798383.20250002</td><td>0.204297672049     </td><td>625000000.0      </td><td>144.0             </td><td>1.0               </td></tr>\n",
       "<tr><td>7      </td><td>1       </td><td>44.0              </td><td>5               </td><td>14            </td><td>27894.0           </td><td>10.0              </td><td>0.493069           </td><td>4          </td><td>19         </td><td>51             </td><td>42600.0           </td><td>0.0               </td><td>0.0                   </td><td>1                 </td><td>19.0              </td><td>2789.4            </td><td>0.06547887323943663  </td><td>361.0             </td><td>1936.0           </td><td>778075236.0       </td><td>0.243117038761     </td><td>1814760000.0     </td><td>100.0             </td><td>0.0               </td></tr>\n",
       "<tr><td>8      </td><td>1       </td><td>33.0              </td><td>3               </td><td>14            </td><td>16116.470000000001</td><td>10.0              </td><td>0.479242           </td><td>4          </td><td>2          </td><td>20             </td><td>20000.0           </td><td>4.0               </td><td>0.0                   </td><td>1                 </td><td>2.0               </td><td>1611.647          </td><td>0.08058235           </td><td>4.0               </td><td>1089.0           </td><td>259740605.26090002</td><td>0.229672894564     </td><td>400000000.0      </td><td>100.0             </td><td>16.0              </td></tr>\n",
       "<tr><td>9      </td><td>1       </td><td>30.0              </td><td>4               </td><td>14            </td><td>3712.77           </td><td>6.0               </td><td>0.36771899999999996</td><td>4          </td><td>29         </td><td>33             </td><td>20000.0           </td><td>3.0               </td><td>0.0                   </td><td>0                 </td><td>29.0              </td><td>618.795           </td><td>0.030939750000000002 </td><td>841.0             </td><td>900.0            </td><td>13784661.072900001</td><td>0.135217262961     </td><td>400000000.0      </td><td>36.0              </td><td>9.0               </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rows:51224\n",
      "Cols:24\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>       </th><th>gender  </th><th>age              </th><th>marital_status  </th><th>job_position  </th><th>credit_sum        </th><th>credit_month      </th><th>score_shk          </th><th>education  </th><th>tariff_id  </th><th>living_region  </th><th>monthly_income    </th><th>credit_count      </th><th>overdue_credit_count  </th><th>open_account_flg  </th><th>tariff            </th><th>dummy_paym        </th><th>dummy_pti           </th><th>tariff_sq        </th><th>age_sq            </th><th>credit_sum_sq     </th><th>score_sq            </th><th>income_sq        </th><th>credit_month_sq   </th><th>credit_count_sq   </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td>type   </td><td>enum    </td><td>int              </td><td>enum            </td><td>enum          </td><td>real              </td><td>int               </td><td>real               </td><td>enum       </td><td>enum       </td><td>enum           </td><td>int               </td><td>int               </td><td>int                   </td><td>enum              </td><td>int               </td><td>real              </td><td>real                </td><td>int              </td><td>int               </td><td>real              </td><td>real                </td><td>int              </td><td>int               </td><td>int               </td></tr>\n",
       "<tr><td>mins   </td><td>        </td><td>18.0             </td><td>                </td><td>              </td><td>3000.0            </td><td>3.0               </td><td>0.0                </td><td>           </td><td>           </td><td>               </td><td>5600.0            </td><td>-1.0              </td><td>-1.0                  </td><td>                  </td><td>1.0               </td><td>125.0             </td><td>0.001216875         </td><td>1.0              </td><td>324.0             </td><td>9000000.0         </td><td>0.0                 </td><td>31360000.0       </td><td>9.0               </td><td>0.0               </td></tr>\n",
       "<tr><td>mean   </td><td>        </td><td>36.53838044666563</td><td>                </td><td>              </td><td>26118.82568561604 </td><td>10.990277994689984</td><td>0.4688726375722327 </td><td>           </td><td>           </td><td>               </td><td>40207.378826331464</td><td>1.9442253631110389</td><td>-0.00903873184444792  </td><td>                  </td><td>14.086346243948173</td><td>2463.416579262655 </td><td>0.07028544053631026 </td><td>334.4080313915331</td><td>1445.9575199125477</td><td>946139290.0099865 </td><td>0.23534455600883497 </td><td>2242404756.003727</td><td>133.61521942839323</td><td>7.237720599718904 </td></tr>\n",
       "<tr><td>maxs   </td><td>        </td><td>71.0             </td><td>                </td><td>              </td><td>200000.0          </td><td>36.0              </td><td>0.9761259999999999 </td><td>           </td><td>           </td><td>               </td><td>950000.0          </td><td>19.0              </td><td>2.0                   </td><td>                  </td><td>99.0              </td><td>29330.0           </td><td>0.9500000000000001  </td><td>9801.0           </td><td>5041.0            </td><td>40000000000.0     </td><td>0.9528219678759999  </td><td>902500000000.0   </td><td>1296.0            </td><td>361.0             </td></tr>\n",
       "<tr><td>sigma  </td><td>        </td><td>10.53121262598734</td><td>                </td><td>              </td><td>16246.580800264084</td><td>3.581795566737427 </td><td>0.12451228213319038</td><td>           </td><td>           </td><td>               </td><td>25015.668300690857</td><td>1.859509569805157 </td><td>0.3148206176572171    </td><td>                  </td><td>11.661283617605509</td><td>1559.109960014688 </td><td>0.04278602318120838 </td><td>387.6242025930971</td><td>859.7691678999645 </td><td>1306010709.7582004</td><td>0.12196280780720098 </td><td>7276206386.54606 </td><td>118.08966130693707</td><td>12.767722775253578</td></tr>\n",
       "<tr><td>zeros  </td><td>        </td><td>0                </td><td>                </td><td>              </td><td>0                 </td><td>0                 </td><td>1                  </td><td>           </td><td>           </td><td>               </td><td>0                 </td><td>7672              </td><td>46200                 </td><td>                  </td><td>0                 </td><td>0                 </td><td>0                   </td><td>0                </td><td>0                 </td><td>0                 </td><td>1                   </td><td>0                </td><td>0                 </td><td>7672              </td></tr>\n",
       "<tr><td>missing</td><td>0       </td><td>0                </td><td>0               </td><td>0             </td><td>0                 </td><td>0                 </td><td>0                  </td><td>0          </td><td>0          </td><td>0              </td><td>0                 </td><td>0                 </td><td>0                     </td><td>0                 </td><td>0                 </td><td>0                 </td><td>0                   </td><td>0                </td><td>0                 </td><td>0                 </td><td>0                   </td><td>0                </td><td>0                 </td><td>0                 </td></tr>\n",
       "<tr><td>0      </td><td>2       </td><td>48.0             </td><td>3               </td><td>15            </td><td>59998.0           </td><td>10.0              </td><td>0.770249           </td><td>2          </td><td>28         </td><td>23             </td><td>30000.0           </td><td>1.0               </td><td>1.0                   </td><td>0                 </td><td>28.0              </td><td>5999.8            </td><td>0.19999333333333333 </td><td>784.0            </td><td>2304.0            </td><td>3599760004.0      </td><td>0.593283522001      </td><td>900000000.0      </td><td>100.0             </td><td>1.0               </td></tr>\n",
       "<tr><td>1      </td><td>1       </td><td>28.0             </td><td>3               </td><td>15            </td><td>10889.0           </td><td>6.0               </td><td>0.24851399999999998</td><td>2          </td><td>2          </td><td>30             </td><td>43000.0           </td><td>2.0               </td><td>0.0                   </td><td>0                 </td><td>2.0               </td><td>1814.8333333333333</td><td>0.042205426356589144</td><td>4.0              </td><td>784.0             </td><td>118570321.0       </td><td>0.061759208196000004</td><td>1849000000.0     </td><td>36.0              </td><td>4.0               </td></tr>\n",
       "<tr><td>2      </td><td>2       </td><td>32.0             </td><td>3               </td><td>14            </td><td>10728.0           </td><td>12.0              </td><td>0.45958899999999997</td><td>4          </td><td>2          </td><td>64             </td><td>23000.0           </td><td>5.0               </td><td>0.0                   </td><td>0                 </td><td>2.0               </td><td>894.0             </td><td>0.0388695652173913  </td><td>4.0              </td><td>1024.0            </td><td>115089984.0       </td><td>0.21122204892100002 </td><td>529000000.0      </td><td>144.0             </td><td>25.0              </td></tr>\n",
       "<tr><td>3      </td><td>2       </td><td>45.0             </td><td>3               </td><td>14            </td><td>16908.89          </td><td>10.0              </td><td>0.42138499999999995</td><td>4          </td><td>2          </td><td>77             </td><td>35000.0           </td><td>1.0               </td><td>0.0                   </td><td>0                 </td><td>2.0               </td><td>1690.8890000000001</td><td>0.04831111428571428 </td><td>4.0              </td><td>2025.0            </td><td>285910561.03209996</td><td>0.17756531822500005 </td><td>1225000000.0     </td><td>100.0             </td><td>1.0               </td></tr>\n",
       "<tr><td>4      </td><td>1       </td><td>32.0             </td><td>4               </td><td>14            </td><td>26268.0           </td><td>10.0              </td><td>0.465026           </td><td>2          </td><td>2          </td><td>68             </td><td>39500.0           </td><td>7.0               </td><td>0.0                   </td><td>0                 </td><td>2.0               </td><td>2626.8            </td><td>0.06650126582278483 </td><td>4.0              </td><td>1024.0            </td><td>690007824.0       </td><td>0.216249180676      </td><td>1560250000.0     </td><td>100.0             </td><td>49.0              </td></tr>\n",
       "<tr><td>5      </td><td>2       </td><td>26.0             </td><td>3               </td><td>14            </td><td>21248.0           </td><td>14.0              </td><td>0.44543            </td><td>4          </td><td>1          </td><td>63             </td><td>36000.0           </td><td>2.0               </td><td>0.0                   </td><td>0                 </td><td>1.0               </td><td>1517.7142857142858</td><td>0.042158730158730166</td><td>1.0              </td><td>676.0             </td><td>451477504.0       </td><td>0.1984078849        </td><td>1296000000.0     </td><td>196.0             </td><td>4.0               </td></tr>\n",
       "<tr><td>6      </td><td>1       </td><td>26.0             </td><td>4               </td><td>14            </td><td>18936.0           </td><td>10.0              </td><td>0.45577399999999996</td><td>2          </td><td>19         </td><td>46             </td><td>30000.0           </td><td>0.0               </td><td>0.0                   </td><td>0                 </td><td>19.0              </td><td>1893.6000000000001</td><td>0.06312000000000001 </td><td>361.0            </td><td>676.0             </td><td>358572096.0       </td><td>0.20772993907600001 </td><td>900000000.0      </td><td>100.0             </td><td>0.0               </td></tr>\n",
       "<tr><td>7      </td><td>2       </td><td>43.0             </td><td>3               </td><td>6             </td><td>57567.0           </td><td>10.0              </td><td>0.34116399999999997</td><td>2          </td><td>2          </td><td>73             </td><td>60000.0           </td><td>7.0               </td><td>0.0                   </td><td>0                 </td><td>2.0               </td><td>5756.700000000001 </td><td>0.095945            </td><td>4.0              </td><td>1849.0            </td><td>3313959489.0      </td><td>0.11639287489600003 </td><td>3600000000.0     </td><td>100.0             </td><td>49.0              </td></tr>\n",
       "<tr><td>8      </td><td>2       </td><td>42.0             </td><td>2               </td><td>14            </td><td>4776.6            </td><td>6.0               </td><td>0.519709           </td><td>4          </td><td>29         </td><td>60             </td><td>27000.0           </td><td>5.0               </td><td>0.0                   </td><td>0                 </td><td>29.0              </td><td>796.1             </td><td>0.02948518518518519 </td><td>841.0            </td><td>1764.0            </td><td>22815907.560000002</td><td>0.270097444681      </td><td>729000000.0      </td><td>36.0              </td><td>25.0              </td></tr>\n",
       "<tr><td>9      </td><td>1       </td><td>34.0             </td><td>4               </td><td>14            </td><td>11462.0           </td><td>6.0               </td><td>0.327044           </td><td>4          </td><td>20         </td><td>31             </td><td>12000.0           </td><td>1.0               </td><td>0.0                   </td><td>1                 </td><td>20.0              </td><td>1910.3333333333333</td><td>0.15919444444444444 </td><td>400.0            </td><td>1156.0            </td><td>131377444.0       </td><td>0.106957777936      </td><td>144000000.0      </td><td>36.0              </td><td>1.0               </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "training = h2o.H2OFrame(train)\n",
    "validation = h2o.H2OFrame(test)\n",
    "\n",
    "training['gender'] = training['gender'].asfactor()\n",
    "training['marital_status'] = training['marital_status'].asfactor()\n",
    "training['job_position'] = training['job_position'].asfactor()\n",
    "training['education'] = training['education'].asfactor()\n",
    "training['tariff_id'] = training['tariff_id'].asfactor()\n",
    "training['living_region'] = training['living_region'].asfactor()\n",
    "training['open_account_flg'] = training['open_account_flg'].asfactor()\n",
    "\n",
    "validation['gender'] = validation['gender'].asfactor()\n",
    "validation['marital_status'] = validation['marital_status'].asfactor()\n",
    "validation['job_position'] = validation['job_position'].asfactor()\n",
    "validation['education'] = validation['education'].asfactor()\n",
    "validation['tariff_id'] = validation['tariff_id'].asfactor()\n",
    "validation['living_region'] = validation['living_region'].asfactor()\n",
    "validation['open_account_flg'] = validation['open_account_flg'].asfactor()\n",
    "\n",
    "X = ['gender', 'age', 'marital_status', 'job_position', 'credit_sum', \n",
    "     'credit_month', 'score_shk', 'education', 'tariff_id', 'living_region', \n",
    "     'monthly_income', 'credit_count', 'overdue_credit_count',\n",
    "     'tariff', 'dummy_paym', 'dummy_pti', 'tariff_sq', 'age_sq', 'credit_sum_sq', \n",
    "     'score_sq', 'income_sq', 'credit_month_sq',  'credit_count_sq']\n",
    "y = 'open_account_flg'\n",
    "\n",
    "training.describe()\n",
    "validation.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "drf Model Build progress: |███████████████████████████████████████████████| 100%\n",
      "Model Details\n",
      "=============\n",
      "H2ORandomForestEstimator :  Distributed Random Forest\n",
      "Model Key:  RF_credit2\n",
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on train data. **\n",
      "\n",
      "MSE: 0.12501709961407625\n",
      "RMSE: 0.35357757227244524\n",
      "LogLoss: 0.3989819427652489\n",
      "Mean Per-Class Error: 0.3038267354904858\n",
      "AUC: 0.7619792652543134\n",
      "Gini: 0.5239585305086267\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21257682873224956: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>73338.0</td>\n",
       "<td>25165.0</td>\n",
       "<td>0.2555</td>\n",
       "<td> (25165.0/98503.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>7625.0</td>\n",
       "<td>13394.0</td>\n",
       "<td>0.3628</td>\n",
       "<td> (7625.0/21019.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>80963.0</td>\n",
       "<td>38559.0</td>\n",
       "<td>0.2743</td>\n",
       "<td> (32790.0/119522.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  ------------------\n",
       "0      73338  25165  0.2555   (25165.0/98503.0)\n",
       "1      7625   13394  0.3628   (7625.0/21019.0)\n",
       "Total  80963  38559  0.2743   (32790.0/119522.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2125768</td>\n",
       "<td>0.4496291</td>\n",
       "<td>228.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1164049</td>\n",
       "<td>0.5962021</td>\n",
       "<td>300.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3195476</td>\n",
       "<td>0.4199711</td>\n",
       "<td>158.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4787491</td>\n",
       "<td>0.8307676</td>\n",
       "<td>86.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.8455481</td>\n",
       "<td>0.8823529</td>\n",
       "<td>10.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0157684</td>\n",
       "<td>1.0</td>\n",
       "<td>394.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9631168</td>\n",
       "<td>0.9999695</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2125768</td>\n",
       "<td>0.3108947</td>\n",
       "<td>228.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1887281</td>\n",
       "<td>0.6949427</td>\n",
       "<td>246.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1769700</td>\n",
       "<td>0.6961733</td>\n",
       "<td>255.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.212577     0.449629  228\n",
       "max f2                       0.116405     0.596202  300\n",
       "max f0point5                 0.319548     0.419971  158\n",
       "max accuracy                 0.478749     0.830768  86\n",
       "max precision                0.845548     0.882353  10\n",
       "max recall                   0.0157684    1         394\n",
       "max specificity              0.963117     0.99997   0\n",
       "max absolute_mcc             0.212577     0.310895  228\n",
       "max min_per_class_accuracy   0.188728     0.694943  246\n",
       "max mean_per_class_accuracy  0.17697      0.696173  255"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,59 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100065</td>\n",
       "<td>0.7375205</td>\n",
       "<td>5.6863790</td>\n",
       "<td>5.6863790</td>\n",
       "<td>1.0</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0569009</td>\n",
       "<td>0.0569009</td>\n",
       "<td>468.6378990</td>\n",
       "<td>468.6378990</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200047</td>\n",
       "<td>0.6463285</td>\n",
       "<td>5.6816205</td>\n",
       "<td>5.6840007</td>\n",
       "<td>0.9991632</td>\n",
       "<td>0.9995818</td>\n",
       "<td>0.0568057</td>\n",
       "<td>0.1137066</td>\n",
       "<td>468.1620514</td>\n",
       "<td>468.4000747</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300028</td>\n",
       "<td>0.5790232</td>\n",
       "<td>5.5816925</td>\n",
       "<td>5.6499075</td>\n",
       "<td>0.9815900</td>\n",
       "<td>0.9935862</td>\n",
       "<td>0.0558067</td>\n",
       "<td>0.1695133</td>\n",
       "<td>458.1692515</td>\n",
       "<td>464.9907513</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400010</td>\n",
       "<td>0.5185305</td>\n",
       "<td>5.5721756</td>\n",
       "<td>5.6304786</td>\n",
       "<td>0.9799163</td>\n",
       "<td>0.9901694</td>\n",
       "<td>0.0557115</td>\n",
       "<td>0.2252248</td>\n",
       "<td>457.2175563</td>\n",
       "<td>463.0478590</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500075</td>\n",
       "<td>0.4724869</td>\n",
       "<td>5.3250372</td>\n",
       "<td>5.5693596</td>\n",
       "<td>0.9364548</td>\n",
       "<td>0.9794211</td>\n",
       "<td>0.0532851</td>\n",
       "<td>0.2785099</td>\n",
       "<td>432.5037182</td>\n",
       "<td>456.9359647</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000067</td>\n",
       "<td>0.3688996</td>\n",
       "<td>3.9032006</td>\n",
       "<td>4.7363498</td>\n",
       "<td>0.6864123</td>\n",
       "<td>0.8329290</td>\n",
       "<td>0.1951568</td>\n",
       "<td>0.4736667</td>\n",
       "<td>290.3200572</td>\n",
       "<td>373.6349806</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500059</td>\n",
       "<td>0.3155777</td>\n",
       "<td>2.4007253</td>\n",
       "<td>3.9578517</td>\n",
       "<td>0.4221888</td>\n",
       "<td>0.6960232</td>\n",
       "<td>0.1200343</td>\n",
       "<td>0.5937009</td>\n",
       "<td>140.0725267</td>\n",
       "<td>295.7851716</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000050</td>\n",
       "<td>0.2733335</td>\n",
       "<td>1.7413108</td>\n",
       "<td>3.4037397</td>\n",
       "<td>0.3062249</td>\n",
       "<td>0.5985777</td>\n",
       "<td>0.0870641</td>\n",
       "<td>0.6807650</td>\n",
       "<td>74.1310835</td>\n",
       "<td>240.3739677</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.3000033</td>\n",
       "<td>0.2113602</td>\n",
       "<td>1.1289974</td>\n",
       "<td>2.6455134</td>\n",
       "<td>0.1985442</td>\n",
       "<td>0.4652369</td>\n",
       "<td>0.1128979</td>\n",
       "<td>0.7936629</td>\n",
       "<td>12.8997435</td>\n",
       "<td>164.5513409</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000017</td>\n",
       "<td>0.1636388</td>\n",
       "<td>0.7107974</td>\n",
       "<td>2.1618445</td>\n",
       "<td>0.125</td>\n",
       "<td>0.3801795</td>\n",
       "<td>0.0710785</td>\n",
       "<td>0.8647414</td>\n",
       "<td>-28.9202626</td>\n",
       "<td>116.1844517</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1226635</td>\n",
       "<td>0.4400854</td>\n",
       "<td>1.8174985</td>\n",
       "<td>0.0773929</td>\n",
       "<td>0.3196232</td>\n",
       "<td>0.0440078</td>\n",
       "<td>0.9087492</td>\n",
       "<td>-55.9914611</td>\n",
       "<td>81.7498454</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999983</td>\n",
       "<td>0.0926832</td>\n",
       "<td>0.3901298</td>\n",
       "<td>1.5796070</td>\n",
       "<td>0.0686078</td>\n",
       "<td>0.2777878</td>\n",
       "<td>0.0390123</td>\n",
       "<td>0.9477615</td>\n",
       "<td>-60.9870250</td>\n",
       "<td>57.9606987</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.6999967</td>\n",
       "<td>0.0755691</td>\n",
       "<td>0.2854608</td>\n",
       "<td>1.3947312</td>\n",
       "<td>0.0502008</td>\n",
       "<td>0.2452758</td>\n",
       "<td>0.0285456</td>\n",
       "<td>0.9763072</td>\n",
       "<td>-71.4539207</td>\n",
       "<td>39.4731169</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999950</td>\n",
       "<td>0.0632443</td>\n",
       "<td>0.1593823</td>\n",
       "<td>1.2403142</td>\n",
       "<td>0.0280288</td>\n",
       "<td>0.2181202</td>\n",
       "<td>0.0159380</td>\n",
       "<td>0.9922451</td>\n",
       "<td>-84.0617724</td>\n",
       "<td>24.0314172</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999933</td>\n",
       "<td>0.0468299</td>\n",
       "<td>0.0642287</td>\n",
       "<td>1.1096392</td>\n",
       "<td>0.0112952</td>\n",
       "<td>0.1951399</td>\n",
       "<td>0.0064228</td>\n",
       "<td>0.9986679</td>\n",
       "<td>-93.5771322</td>\n",
       "<td>10.9639221</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0049956</td>\n",
       "<td>0.0133204</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0023425</td>\n",
       "<td>0.1758588</td>\n",
       "<td>0.0013321</td>\n",
       "<td>1.0</td>\n",
       "<td>-98.6679611</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift       cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  ---------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100065                   0.737521           5.68638    5.68638            1                1                           0.0569009       0.0569009                  468.638   468.638\n",
       "    2        0.0200047                   0.646329           5.68162    5.684              0.999163         0.999582                    0.0568057       0.113707                   468.162   468.4\n",
       "    3        0.0300028                   0.579023           5.58169    5.64991            0.98159          0.993586                    0.0558067       0.169513                   458.169   464.991\n",
       "    4        0.040001                    0.51853            5.57218    5.63048            0.979916         0.990169                    0.0557115       0.225225                   457.218   463.048\n",
       "    5        0.0500075                   0.472487           5.32504    5.56936            0.936455         0.979421                    0.0532851       0.27851                    432.504   456.936\n",
       "    6        0.100007                    0.3689             3.9032     4.73635            0.686412         0.832929                    0.195157        0.473667                   290.32    373.635\n",
       "    7        0.150006                    0.315578           2.40073    3.95785            0.422189         0.696023                    0.120034        0.593701                   140.073   295.785\n",
       "    8        0.200005                    0.273334           1.74131    3.40374            0.306225         0.598578                    0.0870641       0.680765                   74.1311   240.374\n",
       "    9        0.300003                    0.21136            1.129      2.64551            0.198544         0.465237                    0.112898        0.793663                   12.8997   164.551\n",
       "    10       0.400002                    0.163639           0.710797   2.16184            0.125            0.380179                    0.0710785       0.864741                   -28.9203  116.184\n",
       "    11       0.5                         0.122664           0.440085   1.8175             0.0773929        0.319623                    0.0440078       0.908749                   -55.9915  81.7498\n",
       "    12       0.599998                    0.0926832          0.39013    1.57961            0.0686078        0.277788                    0.0390123       0.947762                   -60.987   57.9607\n",
       "    13       0.699997                    0.0755691          0.285461   1.39473            0.0502008        0.245276                    0.0285456       0.976307                   -71.4539  39.4731\n",
       "    14       0.799995                    0.0632443          0.159382   1.24031            0.0280288        0.21812                     0.015938        0.992245                   -84.0618  24.0314\n",
       "    15       0.899993                    0.0468299          0.0642287  1.10964            0.0112952        0.19514                     0.00642276      0.998668                   -93.5771  10.9639\n",
       "    16       1                           0.00499561         0.0133204  1                  0.00234251       0.175859                    0.00133213      1                          -98.668   0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on validation data. **\n",
      "\n",
      "MSE: 0.12484511566163264\n",
      "RMSE: 0.3533342831677003\n",
      "LogLoss: 0.39768226089304004\n",
      "Mean Per-Class Error: 0.30048066419126274\n",
      "AUC: 0.7665055845782554\n",
      "Gini: 0.5330111691565107\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.22460694208828305: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>32339.0</td>\n",
       "<td>9848.0</td>\n",
       "<td>0.2334</td>\n",
       "<td> (9848.0/42187.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>3505.0</td>\n",
       "<td>5532.0</td>\n",
       "<td>0.3878</td>\n",
       "<td> (3505.0/9037.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>35844.0</td>\n",
       "<td>15380.0</td>\n",
       "<td>0.2607</td>\n",
       "<td> (13353.0/51224.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  -----------------\n",
       "0      32339  9848   0.2334   (9848.0/42187.0)\n",
       "1      3505   5532   0.3878   (3505.0/9037.0)\n",
       "Total  35844  15380  0.2607   (13353.0/51224.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2246069</td>\n",
       "<td>0.4531269</td>\n",
       "<td>217.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1237860</td>\n",
       "<td>0.6003226</td>\n",
       "<td>292.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3065130</td>\n",
       "<td>0.4217051</td>\n",
       "<td>165.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.5125907</td>\n",
       "<td>0.8302553</td>\n",
       "<td>70.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.9463924</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0110937</td>\n",
       "<td>1.0</td>\n",
       "<td>397.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9463924</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.1956136</td>\n",
       "<td>0.3153934</td>\n",
       "<td>240.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1905545</td>\n",
       "<td>0.6979875</td>\n",
       "<td>243.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1841045</td>\n",
       "<td>0.6995193</td>\n",
       "<td>247.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.224607     0.453127  217\n",
       "max f2                       0.123786     0.600323  292\n",
       "max f0point5                 0.306513     0.421705  165\n",
       "max accuracy                 0.512591     0.830255  70\n",
       "max precision                0.946392     1         0\n",
       "max recall                   0.0110937    1         397\n",
       "max specificity              0.946392     1         0\n",
       "max absolute_mcc             0.195614     0.315393  240\n",
       "max min_per_class_accuracy   0.190554     0.697988  243\n",
       "max mean_per_class_accuracy  0.184105     0.699519  247"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,64 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100148</td>\n",
       "<td>0.6167697</td>\n",
       "<td>4.1213612</td>\n",
       "<td>4.1213612</td>\n",
       "<td>0.7270955</td>\n",
       "<td>0.7270955</td>\n",
       "<td>0.0412748</td>\n",
       "<td>0.0412748</td>\n",
       "<td>312.1361153</td>\n",
       "<td>312.1361153</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200102</td>\n",
       "<td>0.5247576</td>\n",
       "<td>3.2437462</td>\n",
       "<td>3.6829818</td>\n",
       "<td>0.5722656</td>\n",
       "<td>0.6497561</td>\n",
       "<td>0.0324223</td>\n",
       "<td>0.0736970</td>\n",
       "<td>224.3746196</td>\n",
       "<td>268.2981780</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300055</td>\n",
       "<td>0.4727756</td>\n",
       "<td>2.9559052</td>\n",
       "<td>3.4407806</td>\n",
       "<td>0.5214844</td>\n",
       "<td>0.6070267</td>\n",
       "<td>0.0295452</td>\n",
       "<td>0.1032422</td>\n",
       "<td>195.5905237</td>\n",
       "<td>244.0780615</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400008</td>\n",
       "<td>0.4395836</td>\n",
       "<td>2.6902059</td>\n",
       "<td>3.2532285</td>\n",
       "<td>0.4746094</td>\n",
       "<td>0.5739385</td>\n",
       "<td>0.0268895</td>\n",
       "<td>0.1301317</td>\n",
       "<td>169.0205890</td>\n",
       "<td>225.3228512</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500156</td>\n",
       "<td>0.4177238</td>\n",
       "<td>2.5523711</td>\n",
       "<td>3.1128929</td>\n",
       "<td>0.4502924</td>\n",
       "<td>0.5491803</td>\n",
       "<td>0.0255616</td>\n",
       "<td>0.1556933</td>\n",
       "<td>155.2371116</td>\n",
       "<td>211.2892898</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000117</td>\n",
       "<td>0.3615137</td>\n",
       "<td>2.2974019</td>\n",
       "<td>2.7052270</td>\n",
       "<td>0.4053104</td>\n",
       "<td>0.4772594</td>\n",
       "<td>0.1148611</td>\n",
       "<td>0.2705544</td>\n",
       "<td>129.7401930</td>\n",
       "<td>170.5227005</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500078</td>\n",
       "<td>0.3170659</td>\n",
       "<td>1.9742606</td>\n",
       "<td>2.4616033</td>\n",
       "<td>0.3483014</td>\n",
       "<td>0.4342790</td>\n",
       "<td>0.0987053</td>\n",
       "<td>0.3692597</td>\n",
       "<td>97.4260618</td>\n",
       "<td>146.1603252</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000039</td>\n",
       "<td>0.2799066</td>\n",
       "<td>1.8303963</td>\n",
       "<td>2.3038169</td>\n",
       "<td>0.3229207</td>\n",
       "<td>0.4064422</td>\n",
       "<td>0.0915127</td>\n",
       "<td>0.4607724</td>\n",
       "<td>83.0396335</td>\n",
       "<td>130.3816926</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.2999961</td>\n",
       "<td>0.2238880</td>\n",
       "<td>1.5083617</td>\n",
       "<td>2.0386824</td>\n",
       "<td>0.2661070</td>\n",
       "<td>0.3596668</td>\n",
       "<td>0.1508244</td>\n",
       "<td>0.6115968</td>\n",
       "<td>50.8361672</td>\n",
       "<td>103.8682429</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000078</td>\n",
       "<td>0.1772658</td>\n",
       "<td>1.1661797</td>\n",
       "<td>1.8205354</td>\n",
       "<td>0.2057388</td>\n",
       "<td>0.3211811</td>\n",
       "<td>0.1166316</td>\n",
       "<td>0.7282284</td>\n",
       "<td>16.6179658</td>\n",
       "<td>82.0535445</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1351066</td>\n",
       "<td>0.9096649</td>\n",
       "<td>1.6383756</td>\n",
       "<td>0.1604842</td>\n",
       "<td>0.2890442</td>\n",
       "<td>0.0909594</td>\n",
       "<td>0.8191878</td>\n",
       "<td>-9.0335074</td>\n",
       "<td>63.8375567</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999922</td>\n",
       "<td>0.0989995</td>\n",
       "<td>0.6551358</td>\n",
       "<td>1.4745129</td>\n",
       "<td>0.1155799</td>\n",
       "<td>0.2601354</td>\n",
       "<td>0.0655085</td>\n",
       "<td>0.8846962</td>\n",
       "<td>-34.4864190</td>\n",
       "<td>47.4512938</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.7000039</td>\n",
       "<td>0.0786540</td>\n",
       "<td>0.4812981</td>\n",
       "<td>1.3326093</td>\n",
       "<td>0.0849112</td>\n",
       "<td>0.2351005</td>\n",
       "<td>0.0481354</td>\n",
       "<td>0.9328317</td>\n",
       "<td>-51.8701944</td>\n",
       "<td>33.2609270</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999961</td>\n",
       "<td>0.0653322</td>\n",
       "<td>0.3552341</td>\n",
       "<td>1.2104463</td>\n",
       "<td>0.0626708</td>\n",
       "<td>0.2135484</td>\n",
       "<td>0.0355206</td>\n",
       "<td>0.9683523</td>\n",
       "<td>-64.4765887</td>\n",
       "<td>21.0446319</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999883</td>\n",
       "<td>0.0490537</td>\n",
       "<td>0.2169031</td>\n",
       "<td>1.1000598</td>\n",
       "<td>0.0382663</td>\n",
       "<td>0.1940739</td>\n",
       "<td>0.0216886</td>\n",
       "<td>0.9900409</td>\n",
       "<td>-78.3096928</td>\n",
       "<td>10.0059809</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0049711</td>\n",
       "<td>0.0995789</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0175678</td>\n",
       "<td>0.1764212</td>\n",
       "<td>0.0099591</td>\n",
       "<td>1.0</td>\n",
       "<td>-90.0421092</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift       cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  ---------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100148                   0.61677            4.12136    4.12136            0.727096         0.727096                    0.0412748       0.0412748                  312.136   312.136\n",
       "    2        0.0200102                   0.524758           3.24375    3.68298            0.572266         0.649756                    0.0324223       0.073697                   224.375   268.298\n",
       "    3        0.0300055                   0.472776           2.95591    3.44078            0.521484         0.607027                    0.0295452       0.103242                   195.591   244.078\n",
       "    4        0.0400008                   0.439584           2.69021    3.25323            0.474609         0.573939                    0.0268895       0.130132                   169.021   225.323\n",
       "    5        0.0500156                   0.417724           2.55237    3.11289            0.450292         0.54918                     0.0255616       0.155693                   155.237   211.289\n",
       "    6        0.100012                    0.361514           2.2974     2.70523            0.40531          0.477259                    0.114861        0.270554                   129.74    170.523\n",
       "    7        0.150008                    0.317066           1.97426    2.4616             0.348301         0.434279                    0.0987053       0.36926                    97.4261   146.16\n",
       "    8        0.200004                    0.279907           1.8304     2.30382            0.322921         0.406442                    0.0915127       0.460772                   83.0396   130.382\n",
       "    9        0.299996                    0.223888           1.50836    2.03868            0.266107         0.359667                    0.150824        0.611597                   50.8362   103.868\n",
       "    10       0.400008                    0.177266           1.16618    1.82054            0.205739         0.321181                    0.116632        0.728228                   16.618    82.0535\n",
       "    11       0.5                         0.135107           0.909665   1.63838            0.160484         0.289044                    0.0909594       0.819188                   -9.03351  63.8376\n",
       "    12       0.599992                    0.0989995          0.655136   1.47451            0.11558          0.260135                    0.0655085       0.884696                   -34.4864  47.4513\n",
       "    13       0.700004                    0.078654           0.481298   1.33261            0.0849112        0.235101                    0.0481354       0.932832                   -51.8702  33.2609\n",
       "    14       0.799996                    0.0653322          0.355234   1.21045            0.0626708        0.213548                    0.0355206       0.968352                   -64.4766  21.0446\n",
       "    15       0.899988                    0.0490537          0.216903   1.10006            0.0382663        0.194074                    0.0216886       0.990041                   -78.3097  10.006\n",
       "    16       1                           0.00497107         0.0995789  1                  0.0175678        0.176421                    0.00995906      1                          -90.0421  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Scoring History: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>timestamp</b></td>\n",
       "<td><b>duration</b></td>\n",
       "<td><b>number_of_trees</b></td>\n",
       "<td><b>training_rmse</b></td>\n",
       "<td><b>training_logloss</b></td>\n",
       "<td><b>training_auc</b></td>\n",
       "<td><b>training_lift</b></td>\n",
       "<td><b>training_classification_error</b></td>\n",
       "<td><b>validation_rmse</b></td>\n",
       "<td><b>validation_logloss</b></td>\n",
       "<td><b>validation_auc</b></td>\n",
       "<td><b>validation_lift</b></td>\n",
       "<td><b>validation_classification_error</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:48:51</td>\n",
       "<td> 0.266 sec</td>\n",
       "<td>0.0</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:49:15</td>\n",
       "<td>24.621 sec</td>\n",
       "<td>100.0</td>\n",
       "<td>0.3545854</td>\n",
       "<td>0.4011579</td>\n",
       "<td>0.7576700</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2628386</td>\n",
       "<td>0.3535839</td>\n",
       "<td>0.3982290</td>\n",
       "<td>0.7654217</td>\n",
       "<td>4.0440166</td>\n",
       "<td>0.2760034</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:49:45</td>\n",
       "<td>54.494 sec</td>\n",
       "<td>200.0</td>\n",
       "<td>0.3539191</td>\n",
       "<td>0.3997656</td>\n",
       "<td>0.7604060</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2574338</td>\n",
       "<td>0.3534984</td>\n",
       "<td>0.3980560</td>\n",
       "<td>0.7657797</td>\n",
       "<td>4.0771643</td>\n",
       "<td>0.2730751</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:50:26</td>\n",
       "<td> 1 min 35.291 sec</td>\n",
       "<td>300.0</td>\n",
       "<td>0.3537280</td>\n",
       "<td>0.3993213</td>\n",
       "<td>0.7611684</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2672646</td>\n",
       "<td>0.3534090</td>\n",
       "<td>0.3978927</td>\n",
       "<td>0.7659552</td>\n",
       "<td>4.1545088</td>\n",
       "<td>0.2666133</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:51:16</td>\n",
       "<td> 2 min 24.975 sec</td>\n",
       "<td>400.0</td>\n",
       "<td>0.3536737</td>\n",
       "<td>0.3992122</td>\n",
       "<td>0.7614451</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2654992</td>\n",
       "<td>0.3533942</td>\n",
       "<td>0.3978477</td>\n",
       "<td>0.7661441</td>\n",
       "<td>4.1876565</td>\n",
       "<td>0.2639193</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:52:16</td>\n",
       "<td> 3 min 25.318 sec</td>\n",
       "<td>500.0</td>\n",
       "<td>0.3535645</td>\n",
       "<td>0.3989894</td>\n",
       "<td>0.7619040</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2643530</td>\n",
       "<td>0.3533739</td>\n",
       "<td>0.3977962</td>\n",
       "<td>0.7662753</td>\n",
       "<td>4.1434596</td>\n",
       "<td>0.2718452</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:53:25</td>\n",
       "<td> 4 min 34.128 sec</td>\n",
       "<td>600.0</td>\n",
       "<td>0.3535882</td>\n",
       "<td>0.3990251</td>\n",
       "<td>0.7618653</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2593916</td>\n",
       "<td>0.3533651</td>\n",
       "<td>0.3977556</td>\n",
       "<td>0.7663956</td>\n",
       "<td>4.1545088</td>\n",
       "<td>0.2654615</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:54:44</td>\n",
       "<td> 5 min 53.283 sec</td>\n",
       "<td>700.0</td>\n",
       "<td>0.3535866</td>\n",
       "<td>0.3990003</td>\n",
       "<td>0.7619590</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2641187</td>\n",
       "<td>0.3533649</td>\n",
       "<td>0.3977497</td>\n",
       "<td>0.7664178</td>\n",
       "<td>4.1213612</td>\n",
       "<td>0.2678432</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 22:56:21</td>\n",
       "<td> 7 min 30.518 sec</td>\n",
       "<td>800.0</td>\n",
       "<td>0.3535776</td>\n",
       "<td>0.3989819</td>\n",
       "<td>0.7619793</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2743428</td>\n",
       "<td>0.3533343</td>\n",
       "<td>0.3976823</td>\n",
       "<td>0.7665056</td>\n",
       "<td>4.1213612</td>\n",
       "<td>0.2606786</td></tr></table></div>"
      ],
      "text/plain": [
       "    timestamp            duration          number_of_trees    training_rmse    training_logloss    training_auc    training_lift    training_classification_error    validation_rmse    validation_logloss    validation_auc    validation_lift    validation_classification_error\n",
       "--  -------------------  ----------------  -----------------  ---------------  ------------------  --------------  ---------------  -------------------------------  -----------------  --------------------  ----------------  -----------------  ---------------------------------\n",
       "    2017-07-12 22:48:51  0.266 sec         0                  nan              nan                 nan             nan              nan                              nan                nan                   nan               nan                nan\n",
       "    2017-07-12 22:49:15  24.621 sec        100                0.354585         0.401158            0.75767         5.68638          0.262839                         0.353584           0.398229              0.765422          4.04402            0.276003\n",
       "    2017-07-12 22:49:45  54.494 sec        200                0.353919         0.399766            0.760406        5.68638          0.257434                         0.353498           0.398056              0.76578           4.07716            0.273075\n",
       "    2017-07-12 22:50:26  1 min 35.291 sec  300                0.353728         0.399321            0.761168        5.68638          0.267265                         0.353409           0.397893              0.765955          4.15451            0.266613\n",
       "    2017-07-12 22:51:16  2 min 24.975 sec  400                0.353674         0.399212            0.761445        5.68638          0.265499                         0.353394           0.397848              0.766144          4.18766            0.263919\n",
       "    2017-07-12 22:52:16  3 min 25.318 sec  500                0.353564         0.398989            0.761904        5.68638          0.264353                         0.353374           0.397796              0.766275          4.14346            0.271845\n",
       "    2017-07-12 22:53:25  4 min 34.128 sec  600                0.353588         0.399025            0.761865        5.68638          0.259392                         0.353365           0.397756              0.766396          4.15451            0.265462\n",
       "    2017-07-12 22:54:44  5 min 53.283 sec  700                0.353587         0.399               0.761959        5.68638          0.264119                         0.353365           0.39775               0.766418          4.12136            0.267843\n",
       "    2017-07-12 22:56:21  7 min 30.518 sec  800                0.353578         0.398982            0.761979        5.68638          0.274343                         0.353334           0.397682              0.766506          4.12136            0.260679"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable Importances: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>variable</b></td>\n",
       "<td><b>relative_importance</b></td>\n",
       "<td><b>scaled_importance</b></td>\n",
       "<td><b>percentage</b></td></tr>\n",
       "<tr><td>living_region</td>\n",
       "<td>648523.75</td>\n",
       "<td>1.0</td>\n",
       "<td>0.2278015</td></tr>\n",
       "<tr><td>tariff_id</td>\n",
       "<td>298883.8437500</td>\n",
       "<td>0.4608680</td>\n",
       "<td>0.1049864</td></tr>\n",
       "<tr><td>job_position</td>\n",
       "<td>126872.3593750</td>\n",
       "<td>0.1956326</td>\n",
       "<td>0.0445654</td></tr>\n",
       "<tr><td>score_shk</td>\n",
       "<td>126523.2968750</td>\n",
       "<td>0.1950943</td>\n",
       "<td>0.0444428</td></tr>\n",
       "<tr><td>credit_sum</td>\n",
       "<td>124300.1171875</td>\n",
       "<td>0.1916663</td>\n",
       "<td>0.0436619</td></tr>\n",
       "<tr><td>---</td>\n",
       "<td>---</td>\n",
       "<td>---</td>\n",
       "<td>---</td></tr>\n",
       "<tr><td>marital_status</td>\n",
       "<td>64702.4375000</td>\n",
       "<td>0.0997688</td>\n",
       "<td>0.0227275</td></tr>\n",
       "<tr><td>monthly_income</td>\n",
       "<td>54587.6718750</td>\n",
       "<td>0.0841722</td>\n",
       "<td>0.0191746</td></tr>\n",
       "<tr><td>gender</td>\n",
       "<td>33459.7070312</td>\n",
       "<td>0.0515936</td>\n",
       "<td>0.0117531</td></tr>\n",
       "<tr><td>credit_count_sq</td>\n",
       "<td>30580.8378906</td>\n",
       "<td>0.0471545</td>\n",
       "<td>0.0107419</td></tr>\n",
       "<tr><td>income_sq</td>\n",
       "<td>27604.2988281</td>\n",
       "<td>0.0425648</td>\n",
       "<td>0.0096963</td></tr></table></div>"
      ],
      "text/plain": [
       "variable         relative_importance    scaled_importance    percentage\n",
       "---------------  ---------------------  -------------------  --------------------\n",
       "living_region    648523.75              1.0                  0.22780146135948764\n",
       "tariff_id        298883.84375           0.4608680002081651   0.10498640394124467\n",
       "job_position     126872.359375          0.19563255682617636  0.04456538233449599\n",
       "score_shk        126523.296875          0.19509431516578998  0.044442770097695414\n",
       "credit_sum       124300.1171875         0.19166625306706192  0.04366185254197409\n",
       "---              ---                    ---                  ---\n",
       "marital_status   64702.4375             0.09976880183647861  0.022727478856434963\n",
       "monthly_income   54587.671875           0.08417220167341596  0.01917455054704967\n",
       "gender           33459.70703125         0.05159364947120287  0.01175310874640917\n",
       "credit_count_sq  30580.837890625        0.04715453811926703  0.010741872693300696\n",
       "income_sq        27604.298828125        0.04256482330543022  0.00969632895148538"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "See the whole table with table.as_data_frame()\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf2 = H2ORandomForestEstimator(model_id='RF_credit2', ntrees=800, max_depth=14, score_tree_interval=100, seed=1000000)\n",
    "rf2.train(X, y, training_frame=training, validation_frame=validation)\n",
    "rf2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Выполнение решетчатого поиска с помощью класса H2OGridSearch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "drf Grid Build progress: |████████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "# Импортируем из модуля h2o.grid.grid_search класс H2OGridSearch\n",
    "from h2o.grid.grid_search import H2OGridSearch\n",
    "# Задаем сетку параметров\n",
    "hyper_parameters = {'histogram_type': ['UniformAdaptive', 'Random', \n",
    "                                       'QuantilesGlobal', 'RoundRobin']}\n",
    "# Создаем экземпляр класса H2OGridSearch\n",
    "gridsearch = H2OGridSearch(H2ORandomForestEstimator, grid_id=\"mygrid\",   \n",
    "                           hyper_params=hyper_parameters)\n",
    "# Подгоняем модели решетчатого поиска\n",
    "gridsearch.train(X, y, ntrees=800, max_depth=14, training_frame=training,       \n",
    "                 validation_frame=validation, seed=1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      histogram_type       model_ids              logloss\n",
      "0    UniformAdaptive  mygrid_model_0  0.39768226089304004\n",
      "1         RoundRobin  mygrid_model_3   0.3979140718405067\n",
      "2    QuantilesGlobal  mygrid_model_2  0.39827118264330436\n",
      "3             Random  mygrid_model_1  0.40340004213936953\n"
     ]
    }
   ],
   "source": [
    "gridsearch.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      histogram_type       model_ids                 auc\n",
      "0         RoundRobin  mygrid_model_3  0.7665512771103373\n",
      "1    UniformAdaptive  mygrid_model_0  0.7665055845782554\n",
      "2    QuantilesGlobal  mygrid_model_2  0.7650355139172724\n",
      "3             Random  mygrid_model_1  0.7619142195419516\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gridperf = gridsearch.get_grid(sort_by='auc', decreasing=True)\n",
    "gridperf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Details\n",
      "=============\n",
      "H2ORandomForestEstimator :  Distributed Random Forest\n",
      "Model Key:  mygrid_model_3\n",
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on train data. **\n",
      "\n",
      "MSE: 0.12501530581200213\n",
      "RMSE: 0.3535750356176212\n",
      "LogLoss: 0.3991890097330648\n",
      "Mean Per-Class Error: 0.3035465105019497\n",
      "AUC: 0.761970239854338\n",
      "Gini: 0.523940479708676\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.227331527600663: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>75855.0</td>\n",
       "<td>22648.0</td>\n",
       "<td>0.2299</td>\n",
       "<td> (22648.0/98503.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>8331.0</td>\n",
       "<td>12688.0</td>\n",
       "<td>0.3964</td>\n",
       "<td> (8331.0/21019.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>84186.0</td>\n",
       "<td>35336.0</td>\n",
       "<td>0.2592</td>\n",
       "<td> (30979.0/119522.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  ------------------\n",
       "0      75855  22648  0.2299   (22648.0/98503.0)\n",
       "1      8331   12688  0.3964   (8331.0/21019.0)\n",
       "Total  84186  35336  0.2592   (30979.0/119522.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2273315</td>\n",
       "<td>0.4502884</td>\n",
       "<td>219.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1205554</td>\n",
       "<td>0.5954204</td>\n",
       "<td>297.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3178428</td>\n",
       "<td>0.4194864</td>\n",
       "<td>162.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4690879</td>\n",
       "<td>0.8309684</td>\n",
       "<td>87.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.8569681</td>\n",
       "<td>0.8630137</td>\n",
       "<td>8.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0116974</td>\n",
       "<td>1.0</td>\n",
       "<td>397.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9540265</td>\n",
       "<td>0.9999797</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2273315</td>\n",
       "<td>0.3117821</td>\n",
       "<td>219.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1902499</td>\n",
       "<td>0.6950347</td>\n",
       "<td>244.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1772448</td>\n",
       "<td>0.6964535</td>\n",
       "<td>253.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.227332     0.450288  219\n",
       "max f2                       0.120555     0.59542   297\n",
       "max f0point5                 0.317843     0.419486  162\n",
       "max accuracy                 0.469088     0.830968  87\n",
       "max precision                0.856968     0.863014  8\n",
       "max recall                   0.0116974    1         397\n",
       "max specificity              0.954027     0.99998   0\n",
       "max absolute_mcc             0.227332     0.311782  219\n",
       "max min_per_class_accuracy   0.19025      0.695035  244\n",
       "max mean_per_class_accuracy  0.177245     0.696453  253"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,59 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100065</td>\n",
       "<td>0.7255398</td>\n",
       "<td>5.6863790</td>\n",
       "<td>5.6863790</td>\n",
       "<td>1.0</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0569009</td>\n",
       "<td>0.0569009</td>\n",
       "<td>468.6378990</td>\n",
       "<td>468.6378990</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200047</td>\n",
       "<td>0.6309398</td>\n",
       "<td>5.6816205</td>\n",
       "<td>5.6840007</td>\n",
       "<td>0.9991632</td>\n",
       "<td>0.9995818</td>\n",
       "<td>0.0568057</td>\n",
       "<td>0.1137066</td>\n",
       "<td>468.1620514</td>\n",
       "<td>468.4000747</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300028</td>\n",
       "<td>0.5597506</td>\n",
       "<td>5.5579001</td>\n",
       "<td>5.6419789</td>\n",
       "<td>0.9774059</td>\n",
       "<td>0.9921919</td>\n",
       "<td>0.0555688</td>\n",
       "<td>0.1692754</td>\n",
       "<td>455.7900135</td>\n",
       "<td>464.1978931</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400010</td>\n",
       "<td>0.5042401</td>\n",
       "<td>5.4722476</td>\n",
       "<td>5.5995550</td>\n",
       "<td>0.9623431</td>\n",
       "<td>0.9847312</td>\n",
       "<td>0.0547124</td>\n",
       "<td>0.2239878</td>\n",
       "<td>447.2247564</td>\n",
       "<td>459.9554965</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500075</td>\n",
       "<td>0.4595433</td>\n",
       "<td>5.2061747</td>\n",
       "<td>5.5208394</td>\n",
       "<td>0.9155518</td>\n",
       "<td>0.9708884</td>\n",
       "<td>0.0520957</td>\n",
       "<td>0.2760835</td>\n",
       "<td>420.6174745</td>\n",
       "<td>452.0839431</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000067</td>\n",
       "<td>0.3656776</td>\n",
       "<td>3.8851214</td>\n",
       "<td>4.7030488</td>\n",
       "<td>0.6832329</td>\n",
       "<td>0.8270727</td>\n",
       "<td>0.1942528</td>\n",
       "<td>0.4703364</td>\n",
       "<td>288.5121389</td>\n",
       "<td>370.3048833</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500059</td>\n",
       "<td>0.3156749</td>\n",
       "<td>2.2951048</td>\n",
       "<td>3.9004456</td>\n",
       "<td>0.4036145</td>\n",
       "<td>0.6859278</td>\n",
       "<td>0.1147533</td>\n",
       "<td>0.5850897</td>\n",
       "<td>129.5104773</td>\n",
       "<td>290.0445581</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000050</td>\n",
       "<td>0.2747313</td>\n",
       "<td>1.7251347</td>\n",
       "<td>3.3566406</td>\n",
       "<td>0.3033802</td>\n",
       "<td>0.5902949</td>\n",
       "<td>0.0862553</td>\n",
       "<td>0.6713450</td>\n",
       "<td>72.5134724</td>\n",
       "<td>235.6640616</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.3000033</td>\n",
       "<td>0.2139023</td>\n",
       "<td>1.1508828</td>\n",
       "<td>2.6214085</td>\n",
       "<td>0.2023929</td>\n",
       "<td>0.4609979</td>\n",
       "<td>0.1150864</td>\n",
       "<td>0.7864313</td>\n",
       "<td>15.0882763</td>\n",
       "<td>162.1408504</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000017</td>\n",
       "<td>0.1665987</td>\n",
       "<td>0.7303039</td>\n",
       "<td>2.1486422</td>\n",
       "<td>0.1284304</td>\n",
       "<td>0.3778577</td>\n",
       "<td>0.0730292</td>\n",
       "<td>0.8594605</td>\n",
       "<td>-26.9696139</td>\n",
       "<td>114.8642232</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1247217</td>\n",
       "<td>0.4400854</td>\n",
       "<td>1.8069366</td>\n",
       "<td>0.0773929</td>\n",
       "<td>0.3177658</td>\n",
       "<td>0.0440078</td>\n",
       "<td>0.9034683</td>\n",
       "<td>-55.9914611</td>\n",
       "<td>80.6936581</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999983</td>\n",
       "<td>0.0939096</td>\n",
       "<td>0.3948874</td>\n",
       "<td>1.5715983</td>\n",
       "<td>0.0694444</td>\n",
       "<td>0.2763795</td>\n",
       "<td>0.0394881</td>\n",
       "<td>0.9429564</td>\n",
       "<td>-60.5112570</td>\n",
       "<td>57.1598338</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.6999967</td>\n",
       "<td>0.0771937</td>\n",
       "<td>0.3059188</td>\n",
       "<td>1.3907891</td>\n",
       "<td>0.0537985</td>\n",
       "<td>0.2445826</td>\n",
       "<td>0.0305914</td>\n",
       "<td>0.9735477</td>\n",
       "<td>-69.4081184</td>\n",
       "<td>39.0789139</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999950</td>\n",
       "<td>0.0658875</td>\n",
       "<td>0.1750826</td>\n",
       "<td>1.2388274</td>\n",
       "<td>0.0307898</td>\n",
       "<td>0.2178587</td>\n",
       "<td>0.0175080</td>\n",
       "<td>0.9910557</td>\n",
       "<td>-82.4917380</td>\n",
       "<td>23.8827413</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999933</td>\n",
       "<td>0.0501151</td>\n",
       "<td>0.0765986</td>\n",
       "<td>1.1096921</td>\n",
       "<td>0.0134705</td>\n",
       "<td>0.1951492</td>\n",
       "<td>0.0076597</td>\n",
       "<td>0.9987154</td>\n",
       "<td>-92.3401354</td>\n",
       "<td>10.9692084</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0069006</td>\n",
       "<td>0.0128447</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0022588</td>\n",
       "<td>0.1758588</td>\n",
       "<td>0.0012846</td>\n",
       "<td>1.0</td>\n",
       "<td>-98.7155339</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift       cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  ---------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100065                   0.72554            5.68638    5.68638            1                1                           0.0569009       0.0569009                  468.638   468.638\n",
       "    2        0.0200047                   0.63094            5.68162    5.684              0.999163         0.999582                    0.0568057       0.113707                   468.162   468.4\n",
       "    3        0.0300028                   0.559751           5.5579     5.64198            0.977406         0.992192                    0.0555688       0.169275                   455.79    464.198\n",
       "    4        0.040001                    0.50424            5.47225    5.59955            0.962343         0.984731                    0.0547124       0.223988                   447.225   459.955\n",
       "    5        0.0500075                   0.459543           5.20617    5.52084            0.915552         0.970888                    0.0520957       0.276084                   420.617   452.084\n",
       "    6        0.100007                    0.365678           3.88512    4.70305            0.683233         0.827073                    0.194253        0.470336                   288.512   370.305\n",
       "    7        0.150006                    0.315675           2.2951     3.90045            0.403614         0.685928                    0.114753        0.58509                    129.51    290.045\n",
       "    8        0.200005                    0.274731           1.72513    3.35664            0.30338          0.590295                    0.0862553       0.671345                   72.5135   235.664\n",
       "    9        0.300003                    0.213902           1.15088    2.62141            0.202393         0.460998                    0.115086        0.786431                   15.0883   162.141\n",
       "    10       0.400002                    0.166599           0.730304   2.14864            0.12843          0.377858                    0.0730292       0.85946                    -26.9696  114.864\n",
       "    11       0.5                         0.124722           0.440085   1.80694            0.0773929        0.317766                    0.0440078       0.903468                   -55.9915  80.6937\n",
       "    12       0.599998                    0.0939096          0.394887   1.5716             0.0694444        0.276379                    0.0394881       0.942956                   -60.5113  57.1598\n",
       "    13       0.699997                    0.0771937          0.305919   1.39079            0.0537985        0.244583                    0.0305914       0.973548                   -69.4081  39.0789\n",
       "    14       0.799995                    0.0658875          0.175083   1.23883            0.0307898        0.217859                    0.017508        0.991056                   -82.4917  23.8827\n",
       "    15       0.899993                    0.0501151          0.0765986  1.10969            0.0134705        0.195149                    0.00765974      0.998715                   -92.3401  10.9692\n",
       "    16       1                           0.00690056         0.0128447  1                  0.00225885       0.175859                    0.00128455      1                          -98.7155  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on validation data. **\n",
      "\n",
      "MSE: 0.12483107919936037\n",
      "RMSE: 0.3533144197444542\n",
      "LogLoss: 0.3979140718405067\n",
      "Mean Per-Class Error: 0.3009806315100858\n",
      "AUC: 0.7665512771103373\n",
      "Gini: 0.5331025542206747\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.22745429493160918: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>32454.0</td>\n",
       "<td>9733.0</td>\n",
       "<td>0.2307</td>\n",
       "<td> (9733.0/42187.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>3504.0</td>\n",
       "<td>5533.0</td>\n",
       "<td>0.3877</td>\n",
       "<td> (3504.0/9037.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>35958.0</td>\n",
       "<td>15266.0</td>\n",
       "<td>0.2584</td>\n",
       "<td> (13237.0/51224.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  -----------------\n",
       "0      32454  9733   0.2307   (9733.0/42187.0)\n",
       "1      3504   5533   0.3877   (3504.0/9037.0)\n",
       "Total  35958  15266  0.2584   (13237.0/51224.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2274543</td>\n",
       "<td>0.4553347</td>\n",
       "<td>216.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1142319</td>\n",
       "<td>0.6001856</td>\n",
       "<td>302.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3154891</td>\n",
       "<td>0.4207902</td>\n",
       "<td>157.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4531076</td>\n",
       "<td>0.8305677</td>\n",
       "<td>88.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.9150186</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0127408</td>\n",
       "<td>1.0</td>\n",
       "<td>397.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9150186</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2274543</td>\n",
       "<td>0.3179745</td>\n",
       "<td>216.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1924641</td>\n",
       "<td>0.6985801</td>\n",
       "<td>241.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1807626</td>\n",
       "<td>0.6990194</td>\n",
       "<td>250.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.227454     0.455335  216\n",
       "max f2                       0.114232     0.600186  302\n",
       "max f0point5                 0.315489     0.42079   157\n",
       "max accuracy                 0.453108     0.830568  88\n",
       "max precision                0.915019     1         0\n",
       "max recall                   0.0127408    1         397\n",
       "max specificity              0.915019     1         0\n",
       "max absolute_mcc             0.227454     0.317975  216\n",
       "max min_per_class_accuracy   0.192464     0.69858   241\n",
       "max mean_per_class_accuracy  0.180763     0.699019  250"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,64 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100148</td>\n",
       "<td>0.6075336</td>\n",
       "<td>4.1766073</td>\n",
       "<td>4.1766073</td>\n",
       "<td>0.7368421</td>\n",
       "<td>0.7368421</td>\n",
       "<td>0.0418280</td>\n",
       "<td>0.0418280</td>\n",
       "<td>317.6607281</td>\n",
       "<td>317.6607281</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200102</td>\n",
       "<td>0.5192058</td>\n",
       "<td>3.0998257</td>\n",
       "<td>3.6387418</td>\n",
       "<td>0.546875</td>\n",
       "<td>0.6419512</td>\n",
       "<td>0.0309837</td>\n",
       "<td>0.0728118</td>\n",
       "<td>209.9825716</td>\n",
       "<td>263.8741758</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300055</td>\n",
       "<td>0.4681068</td>\n",
       "<td>3.1773214</td>\n",
       "<td>3.4850350</td>\n",
       "<td>0.5605469</td>\n",
       "<td>0.6148341</td>\n",
       "<td>0.0317583</td>\n",
       "<td>0.1045701</td>\n",
       "<td>217.7321359</td>\n",
       "<td>248.5035028</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400008</td>\n",
       "<td>0.4329442</td>\n",
       "<td>2.5462854</td>\n",
       "<td>3.2504622</td>\n",
       "<td>0.4492188</td>\n",
       "<td>0.5734505</td>\n",
       "<td>0.0254509</td>\n",
       "<td>0.1300210</td>\n",
       "<td>154.6285410</td>\n",
       "<td>225.0462161</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500156</td>\n",
       "<td>0.4125622</td>\n",
       "<td>2.5192234</td>\n",
       "<td>3.1040432</td>\n",
       "<td>0.4444444</td>\n",
       "<td>0.5476190</td>\n",
       "<td>0.0252296</td>\n",
       "<td>0.1552506</td>\n",
       "<td>151.9223439</td>\n",
       "<td>210.4043166</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000117</td>\n",
       "<td>0.3586610</td>\n",
       "<td>2.3062551</td>\n",
       "<td>2.7052270</td>\n",
       "<td>0.4068723</td>\n",
       "<td>0.4772594</td>\n",
       "<td>0.1153038</td>\n",
       "<td>0.2705544</td>\n",
       "<td>130.6255117</td>\n",
       "<td>170.5227005</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500078</td>\n",
       "<td>0.3166723</td>\n",
       "<td>1.9919670</td>\n",
       "<td>2.4675046</td>\n",
       "<td>0.3514252</td>\n",
       "<td>0.4353201</td>\n",
       "<td>0.0995906</td>\n",
       "<td>0.3701450</td>\n",
       "<td>99.1966991</td>\n",
       "<td>146.7504608</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000039</td>\n",
       "<td>0.2810350</td>\n",
       "<td>1.8171166</td>\n",
       "<td>2.3049235</td>\n",
       "<td>0.3205779</td>\n",
       "<td>0.4066374</td>\n",
       "<td>0.0908487</td>\n",
       "<td>0.4609937</td>\n",
       "<td>81.7116555</td>\n",
       "<td>130.4923466</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.2999961</td>\n",
       "<td>0.2257051</td>\n",
       "<td>1.5327079</td>\n",
       "<td>2.0475350</td>\n",
       "<td>0.2704022</td>\n",
       "<td>0.3612286</td>\n",
       "<td>0.1532588</td>\n",
       "<td>0.6142525</td>\n",
       "<td>53.2707935</td>\n",
       "<td>104.7535040</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000078</td>\n",
       "<td>0.1787912</td>\n",
       "<td>1.1318803</td>\n",
       "<td>1.8185990</td>\n",
       "<td>0.1996877</td>\n",
       "<td>0.3208394</td>\n",
       "<td>0.1132013</td>\n",
       "<td>0.7274538</td>\n",
       "<td>13.1880256</td>\n",
       "<td>81.8599000</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1373174</td>\n",
       "<td>0.9074516</td>\n",
       "<td>1.6363838</td>\n",
       "<td>0.1600937</td>\n",
       "<td>0.2886928</td>\n",
       "<td>0.0907381</td>\n",
       "<td>0.8181919</td>\n",
       "<td>-9.2548371</td>\n",
       "<td>63.6383756</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999922</td>\n",
       "<td>0.0997335</td>\n",
       "<td>0.6650956</td>\n",
       "<td>1.4745129</td>\n",
       "<td>0.1173370</td>\n",
       "<td>0.2601354</td>\n",
       "<td>0.0665044</td>\n",
       "<td>0.8846962</td>\n",
       "<td>-33.4904355</td>\n",
       "<td>47.4512938</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.7000039</td>\n",
       "<td>0.0797965</td>\n",
       "<td>0.4746595</td>\n",
       "<td>1.3316608</td>\n",
       "<td>0.0837400</td>\n",
       "<td>0.2349332</td>\n",
       "<td>0.0474715</td>\n",
       "<td>0.9321678</td>\n",
       "<td>-52.5340538</td>\n",
       "<td>33.1660793</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999961</td>\n",
       "<td>0.0675917</td>\n",
       "<td>0.3574474</td>\n",
       "<td>1.2098930</td>\n",
       "<td>0.0630613</td>\n",
       "<td>0.2134508</td>\n",
       "<td>0.0357419</td>\n",
       "<td>0.9679097</td>\n",
       "<td>-64.2552590</td>\n",
       "<td>20.9893036</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999883</td>\n",
       "<td>0.0517834</td>\n",
       "<td>0.2202230</td>\n",
       "<td>1.0999369</td>\n",
       "<td>0.0388520</td>\n",
       "<td>0.1940522</td>\n",
       "<td>0.0220206</td>\n",
       "<td>0.9899303</td>\n",
       "<td>-77.9776983</td>\n",
       "<td>9.9936856</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0070596</td>\n",
       "<td>0.1006853</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0177630</td>\n",
       "<td>0.1764212</td>\n",
       "<td>0.0100697</td>\n",
       "<td>1.0</td>\n",
       "<td>-89.9314660</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift      cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  --------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100148                   0.607534           4.17661   4.17661            0.736842         0.736842                    0.041828        0.041828                   317.661   317.661\n",
       "    2        0.0200102                   0.519206           3.09983   3.63874            0.546875         0.641951                    0.0309837       0.0728118                  209.983   263.874\n",
       "    3        0.0300055                   0.468107           3.17732   3.48504            0.560547         0.614834                    0.0317583       0.10457                    217.732   248.504\n",
       "    4        0.0400008                   0.432944           2.54629   3.25046            0.449219         0.57345                     0.0254509       0.130021                   154.629   225.046\n",
       "    5        0.0500156                   0.412562           2.51922   3.10404            0.444444         0.547619                    0.0252296       0.155251                   151.922   210.404\n",
       "    6        0.100012                    0.358661           2.30626   2.70523            0.406872         0.477259                    0.115304        0.270554                   130.626   170.523\n",
       "    7        0.150008                    0.316672           1.99197   2.4675             0.351425         0.43532                     0.0995906       0.370145                   99.1967   146.75\n",
       "    8        0.200004                    0.281035           1.81712   2.30492            0.320578         0.406637                    0.0908487       0.460994                   81.7117   130.492\n",
       "    9        0.299996                    0.225705           1.53271   2.04754            0.270402         0.361229                    0.153259        0.614253                   53.2708   104.754\n",
       "    10       0.400008                    0.178791           1.13188   1.8186             0.199688         0.320839                    0.113201        0.727454                   13.188    81.8599\n",
       "    11       0.5                         0.137317           0.907452  1.63638            0.160094         0.288693                    0.0907381       0.818192                   -9.25484  63.6384\n",
       "    12       0.599992                    0.0997335          0.665096  1.47451            0.117337         0.260135                    0.0665044       0.884696                   -33.4904  47.4513\n",
       "    13       0.700004                    0.0797965          0.474659  1.33166            0.08374          0.234933                    0.0474715       0.932168                   -52.5341  33.1661\n",
       "    14       0.799996                    0.0675917          0.357447  1.20989            0.0630613        0.213451                    0.0357419       0.96791                    -64.2553  20.9893\n",
       "    15       0.899988                    0.0517834          0.220223  1.09994            0.038852         0.194052                    0.0220206       0.98993                    -77.9777  9.99369\n",
       "    16       1                           0.00705962         0.100685  1                  0.017763         0.176421                    0.0100697       1                          -89.9315  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Scoring History: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>timestamp</b></td>\n",
       "<td><b>duration</b></td>\n",
       "<td><b>number_of_trees</b></td>\n",
       "<td><b>training_rmse</b></td>\n",
       "<td><b>training_logloss</b></td>\n",
       "<td><b>training_auc</b></td>\n",
       "<td><b>training_lift</b></td>\n",
       "<td><b>training_classification_error</b></td>\n",
       "<td><b>validation_rmse</b></td>\n",
       "<td><b>validation_logloss</b></td>\n",
       "<td><b>validation_auc</b></td>\n",
       "<td><b>validation_lift</b></td>\n",
       "<td><b>validation_classification_error</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 23:16:22</td>\n",
       "<td>18 min 20.504 sec</td>\n",
       "<td>0.0</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 23:16:22</td>\n",
       "<td>18 min 21.204 sec</td>\n",
       "<td>1.0</td>\n",
       "<td>0.3914979</td>\n",
       "<td>1.7137480</td>\n",
       "<td>0.6606974</td>\n",
       "<td>4.1345559</td>\n",
       "<td>0.2917141</td>\n",
       "<td>0.3883276</td>\n",
       "<td>1.6265088</td>\n",
       "<td>0.6701004</td>\n",
       "<td>2.3487436</td>\n",
       "<td>0.2998594</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 23:16:23</td>\n",
       "<td>18 min 21.698 sec</td>\n",
       "<td>2.0</td>\n",
       "<td>0.3877207</td>\n",
       "<td>1.4859533</td>\n",
       "<td>0.6672446</td>\n",
       "<td>5.3587687</td>\n",
       "<td>0.2949230</td>\n",
       "<td>0.3712470</td>\n",
       "<td>0.6731222</td>\n",
       "<td>0.7077018</td>\n",
       "<td>3.1269308</td>\n",
       "<td>0.2948813</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 23:16:24</td>\n",
       "<td>18 min 22.859 sec</td>\n",
       "<td>3.0</td>\n",
       "<td>0.3831936</td>\n",
       "<td>1.2484785</td>\n",
       "<td>0.6797248</td>\n",
       "<td>5.5248611</td>\n",
       "<td>0.2923736</td>\n",
       "<td>0.3658625</td>\n",
       "<td>0.4866217</td>\n",
       "<td>0.7227650</td>\n",
       "<td>3.5357522</td>\n",
       "<td>0.2755349</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 23:16:25</td>\n",
       "<td>18 min 24.040 sec</td>\n",
       "<td>4.0</td>\n",
       "<td>0.3808052</td>\n",
       "<td>1.1266968</td>\n",
       "<td>0.6838215</td>\n",
       "<td>5.5865345</td>\n",
       "<td>0.3144572</td>\n",
       "<td>0.3626566</td>\n",
       "<td>0.4353914</td>\n",
       "<td>0.7327566</td>\n",
       "<td>3.6462445</td>\n",
       "<td>0.2813915</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 23:16:35</td>\n",
       "<td>18 min 34.228 sec</td>\n",
       "<td>35.0</td>\n",
       "<td>0.3567636</td>\n",
       "<td>0.4064150</td>\n",
       "<td>0.7488123</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2769950</td>\n",
       "<td>0.3542683</td>\n",
       "<td>0.3999516</td>\n",
       "<td>0.7619157</td>\n",
       "<td>4.0771643</td>\n",
       "<td>0.2713962</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 23:17:15</td>\n",
       "<td>19 min 13.934 sec</td>\n",
       "<td>169.0</td>\n",
       "<td>0.3541757</td>\n",
       "<td>0.4004267</td>\n",
       "<td>0.7594667</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2694650</td>\n",
       "<td>0.3534541</td>\n",
       "<td>0.3982250</td>\n",
       "<td>0.7660022</td>\n",
       "<td>4.0882135</td>\n",
       "<td>0.2565594</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 23:20:02</td>\n",
       "<td>22 min  0.993 sec</td>\n",
       "<td>686.0</td>\n",
       "<td>0.3535958</td>\n",
       "<td>0.3992369</td>\n",
       "<td>0.7618795</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2590402</td>\n",
       "<td>0.3533196</td>\n",
       "<td>0.3979303</td>\n",
       "<td>0.7665741</td>\n",
       "<td>4.1655581</td>\n",
       "<td>0.2604053</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-12 23:22:09</td>\n",
       "<td>24 min  7.770 sec</td>\n",
       "<td>800.0</td>\n",
       "<td>0.3535750</td>\n",
       "<td>0.3991890</td>\n",
       "<td>0.7619702</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2591908</td>\n",
       "<td>0.3533144</td>\n",
       "<td>0.3979141</td>\n",
       "<td>0.7665513</td>\n",
       "<td>4.1766073</td>\n",
       "<td>0.2584140</td></tr></table></div>"
      ],
      "text/plain": [
       "    timestamp            duration           number_of_trees    training_rmse    training_logloss    training_auc    training_lift    training_classification_error    validation_rmse    validation_logloss    validation_auc    validation_lift    validation_classification_error\n",
       "--  -------------------  -----------------  -----------------  ---------------  ------------------  --------------  ---------------  -------------------------------  -----------------  --------------------  ----------------  -----------------  ---------------------------------\n",
       "    2017-07-12 23:16:22  18 min 20.504 sec  0                  nan              nan                 nan             nan              nan                              nan                nan                   nan               nan                nan\n",
       "    2017-07-12 23:16:22  18 min 21.204 sec  1                  0.391498         1.71375             0.660697        4.13456          0.291714                         0.388328           1.62651               0.6701            2.34874            0.299859\n",
       "    2017-07-12 23:16:23  18 min 21.698 sec  2                  0.387721         1.48595             0.667245        5.35877          0.294923                         0.371247           0.673122              0.707702          3.12693            0.294881\n",
       "    2017-07-12 23:16:24  18 min 22.859 sec  3                  0.383194         1.24848             0.679725        5.52486          0.292374                         0.365862           0.486622              0.722765          3.53575            0.275535\n",
       "    2017-07-12 23:16:25  18 min 24.040 sec  4                  0.380805         1.1267              0.683821        5.58653          0.314457                         0.362657           0.435391              0.732757          3.64624            0.281392\n",
       "    2017-07-12 23:16:35  18 min 34.228 sec  35                 0.356764         0.406415            0.748812        5.68638          0.276995                         0.354268           0.399952              0.761916          4.07716            0.271396\n",
       "    2017-07-12 23:17:15  19 min 13.934 sec  169                0.354176         0.400427            0.759467        5.68638          0.269465                         0.353454           0.398225              0.766002          4.08821            0.256559\n",
       "    2017-07-12 23:20:02  22 min  0.993 sec  686                0.353596         0.399237            0.761879        5.68638          0.25904                          0.35332            0.39793               0.766574          4.16556            0.260405\n",
       "    2017-07-12 23:22:09  24 min  7.770 sec  800                0.353575         0.399189            0.76197         5.68638          0.259191                         0.353314           0.397914              0.766551          4.17661            0.258414"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable Importances: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>variable</b></td>\n",
       "<td><b>relative_importance</b></td>\n",
       "<td><b>scaled_importance</b></td>\n",
       "<td><b>percentage</b></td></tr>\n",
       "<tr><td>living_region</td>\n",
       "<td>617798.4375000</td>\n",
       "<td>1.0</td>\n",
       "<td>0.2153596</td></tr>\n",
       "<tr><td>tariff_id</td>\n",
       "<td>303094.8750000</td>\n",
       "<td>0.4906048</td>\n",
       "<td>0.1056564</td></tr>\n",
       "<tr><td>score_shk</td>\n",
       "<td>130313.2734375</td>\n",
       "<td>0.2109317</td>\n",
       "<td>0.0454262</td></tr>\n",
       "<tr><td>score_sq</td>\n",
       "<td>128976.0234375</td>\n",
       "<td>0.2087672</td>\n",
       "<td>0.0449600</td></tr>\n",
       "<tr><td>credit_sum</td>\n",
       "<td>126562.0781250</td>\n",
       "<td>0.2048598</td>\n",
       "<td>0.0441185</td></tr>\n",
       "<tr><td>---</td>\n",
       "<td>---</td>\n",
       "<td>---</td>\n",
       "<td>---</td></tr>\n",
       "<tr><td>monthly_income</td>\n",
       "<td>61428.6171875</td>\n",
       "<td>0.0994315</td>\n",
       "<td>0.0214135</td></tr>\n",
       "<tr><td>marital_status</td>\n",
       "<td>55896.8671875</td>\n",
       "<td>0.0904775</td>\n",
       "<td>0.0194852</td></tr>\n",
       "<tr><td>income_sq</td>\n",
       "<td>45024.8007812</td>\n",
       "<td>0.0728794</td>\n",
       "<td>0.0156953</td></tr>\n",
       "<tr><td>credit_count_sq</td>\n",
       "<td>31475.5703125</td>\n",
       "<td>0.0509480</td>\n",
       "<td>0.0109721</td></tr>\n",
       "<tr><td>gender</td>\n",
       "<td>30829.8085938</td>\n",
       "<td>0.0499027</td>\n",
       "<td>0.0107470</td></tr></table></div>"
      ],
      "text/plain": [
       "variable         relative_importance    scaled_importance     percentage\n",
       "---------------  ---------------------  --------------------  --------------------\n",
       "living_region    617798.4375            1.0                   0.21535958086607487\n",
       "tariff_id        303094.875             0.490604793735821     0.10565644274983352\n",
       "score_shk        130313.2734375         0.21093169799009082   0.04542616207051545\n",
       "score_sq         128976.0234375         0.20876715706730806   0.044960007444617485\n",
       "credit_sum       126562.078125          0.20485982230248034   0.04411852546736074\n",
       "---              ---                    ---                   ---\n",
       "monthly_income   61428.6171875          0.09943148680673056   0.021413523323588146\n",
       "marital_status   55896.8671875          0.09047751466270097   0.019485199635563423\n",
       "income_sq        45024.80078125         0.07287943453442289   0.015695284475089857\n",
       "credit_count_sq  31475.5703125          0.05094796037340253   0.01097213139199736\n",
       "gender           30829.80859375         0.049902697582898954  0.010747024035539607"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "See the whole table with table.as_data_frame()\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_model = gridperf.models[0]\n",
    "best_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "drf Grid Build progress: |████████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "hyper_parameters2 = {'histogram_type': ['UniformAdaptive', 'RoundRobin']}\n",
    "gridsearch2 = H2OGridSearch(H2ORandomForestEstimator, grid_id=\"mygrid2\",\n",
    "                           hyper_params=hyper_parameters2)\n",
    "gridsearch2.train(X, y, ntrees=800, max_depth=14, training_frame=training,       \n",
    "                  validation_frame=validation, nfolds=5,\n",
    "                  keep_cross_validation_predictions=True, seed=1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      histogram_type        model_ids                 auc\n",
      "0         RoundRobin  mygrid2_model_1  0.7612882132260508\n",
      "1    UniformAdaptive  mygrid2_model_0  0.7612664559578253\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gridperf2 = gridsearch2.get_grid(sort_by='auc', decreasing=True)\n",
    "gridperf2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Details\n",
      "=============\n",
      "H2ORandomForestEstimator :  Distributed Random Forest\n",
      "Model Key:  mygrid2_model_1\n",
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on train data. **\n",
      "\n",
      "MSE: 0.12501530581200213\n",
      "RMSE: 0.3535750356176212\n",
      "LogLoss: 0.3991890097330648\n",
      "Mean Per-Class Error: 0.3035465105019497\n",
      "AUC: 0.761970239854338\n",
      "Gini: 0.523940479708676\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.227331527600663: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>75855.0</td>\n",
       "<td>22648.0</td>\n",
       "<td>0.2299</td>\n",
       "<td> (22648.0/98503.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>8331.0</td>\n",
       "<td>12688.0</td>\n",
       "<td>0.3964</td>\n",
       "<td> (8331.0/21019.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>84186.0</td>\n",
       "<td>35336.0</td>\n",
       "<td>0.2592</td>\n",
       "<td> (30979.0/119522.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  ------------------\n",
       "0      75855  22648  0.2299   (22648.0/98503.0)\n",
       "1      8331   12688  0.3964   (8331.0/21019.0)\n",
       "Total  84186  35336  0.2592   (30979.0/119522.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2273315</td>\n",
       "<td>0.4502884</td>\n",
       "<td>219.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1205554</td>\n",
       "<td>0.5954204</td>\n",
       "<td>297.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3178428</td>\n",
       "<td>0.4194864</td>\n",
       "<td>162.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4690879</td>\n",
       "<td>0.8309684</td>\n",
       "<td>87.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.8569681</td>\n",
       "<td>0.8630137</td>\n",
       "<td>8.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0116974</td>\n",
       "<td>1.0</td>\n",
       "<td>397.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9540265</td>\n",
       "<td>0.9999797</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2273315</td>\n",
       "<td>0.3117821</td>\n",
       "<td>219.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1902499</td>\n",
       "<td>0.6950347</td>\n",
       "<td>244.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1772448</td>\n",
       "<td>0.6964535</td>\n",
       "<td>253.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.227332     0.450288  219\n",
       "max f2                       0.120555     0.59542   297\n",
       "max f0point5                 0.317843     0.419486  162\n",
       "max accuracy                 0.469088     0.830968  87\n",
       "max precision                0.856968     0.863014  8\n",
       "max recall                   0.0116974    1         397\n",
       "max specificity              0.954027     0.99998   0\n",
       "max absolute_mcc             0.227332     0.311782  219\n",
       "max min_per_class_accuracy   0.19025      0.695035  244\n",
       "max mean_per_class_accuracy  0.177245     0.696453  253"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,59 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100065</td>\n",
       "<td>0.7255398</td>\n",
       "<td>5.6863790</td>\n",
       "<td>5.6863790</td>\n",
       "<td>1.0</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0569009</td>\n",
       "<td>0.0569009</td>\n",
       "<td>468.6378990</td>\n",
       "<td>468.6378990</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200047</td>\n",
       "<td>0.6309398</td>\n",
       "<td>5.6816205</td>\n",
       "<td>5.6840007</td>\n",
       "<td>0.9991632</td>\n",
       "<td>0.9995818</td>\n",
       "<td>0.0568057</td>\n",
       "<td>0.1137066</td>\n",
       "<td>468.1620514</td>\n",
       "<td>468.4000747</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300028</td>\n",
       "<td>0.5597506</td>\n",
       "<td>5.5579001</td>\n",
       "<td>5.6419789</td>\n",
       "<td>0.9774059</td>\n",
       "<td>0.9921919</td>\n",
       "<td>0.0555688</td>\n",
       "<td>0.1692754</td>\n",
       "<td>455.7900135</td>\n",
       "<td>464.1978931</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400010</td>\n",
       "<td>0.5042401</td>\n",
       "<td>5.4722476</td>\n",
       "<td>5.5995550</td>\n",
       "<td>0.9623431</td>\n",
       "<td>0.9847312</td>\n",
       "<td>0.0547124</td>\n",
       "<td>0.2239878</td>\n",
       "<td>447.2247564</td>\n",
       "<td>459.9554965</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500075</td>\n",
       "<td>0.4595433</td>\n",
       "<td>5.2061747</td>\n",
       "<td>5.5208394</td>\n",
       "<td>0.9155518</td>\n",
       "<td>0.9708884</td>\n",
       "<td>0.0520957</td>\n",
       "<td>0.2760835</td>\n",
       "<td>420.6174745</td>\n",
       "<td>452.0839431</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000067</td>\n",
       "<td>0.3656776</td>\n",
       "<td>3.8851214</td>\n",
       "<td>4.7030488</td>\n",
       "<td>0.6832329</td>\n",
       "<td>0.8270727</td>\n",
       "<td>0.1942528</td>\n",
       "<td>0.4703364</td>\n",
       "<td>288.5121389</td>\n",
       "<td>370.3048833</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500059</td>\n",
       "<td>0.3156749</td>\n",
       "<td>2.2951048</td>\n",
       "<td>3.9004456</td>\n",
       "<td>0.4036145</td>\n",
       "<td>0.6859278</td>\n",
       "<td>0.1147533</td>\n",
       "<td>0.5850897</td>\n",
       "<td>129.5104773</td>\n",
       "<td>290.0445581</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000050</td>\n",
       "<td>0.2747313</td>\n",
       "<td>1.7251347</td>\n",
       "<td>3.3566406</td>\n",
       "<td>0.3033802</td>\n",
       "<td>0.5902949</td>\n",
       "<td>0.0862553</td>\n",
       "<td>0.6713450</td>\n",
       "<td>72.5134724</td>\n",
       "<td>235.6640616</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.3000033</td>\n",
       "<td>0.2139023</td>\n",
       "<td>1.1508828</td>\n",
       "<td>2.6214085</td>\n",
       "<td>0.2023929</td>\n",
       "<td>0.4609979</td>\n",
       "<td>0.1150864</td>\n",
       "<td>0.7864313</td>\n",
       "<td>15.0882763</td>\n",
       "<td>162.1408504</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000017</td>\n",
       "<td>0.1665987</td>\n",
       "<td>0.7303039</td>\n",
       "<td>2.1486422</td>\n",
       "<td>0.1284304</td>\n",
       "<td>0.3778577</td>\n",
       "<td>0.0730292</td>\n",
       "<td>0.8594605</td>\n",
       "<td>-26.9696139</td>\n",
       "<td>114.8642232</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1247217</td>\n",
       "<td>0.4400854</td>\n",
       "<td>1.8069366</td>\n",
       "<td>0.0773929</td>\n",
       "<td>0.3177658</td>\n",
       "<td>0.0440078</td>\n",
       "<td>0.9034683</td>\n",
       "<td>-55.9914611</td>\n",
       "<td>80.6936581</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999983</td>\n",
       "<td>0.0939096</td>\n",
       "<td>0.3948874</td>\n",
       "<td>1.5715983</td>\n",
       "<td>0.0694444</td>\n",
       "<td>0.2763795</td>\n",
       "<td>0.0394881</td>\n",
       "<td>0.9429564</td>\n",
       "<td>-60.5112570</td>\n",
       "<td>57.1598338</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.6999967</td>\n",
       "<td>0.0771937</td>\n",
       "<td>0.3059188</td>\n",
       "<td>1.3907891</td>\n",
       "<td>0.0537985</td>\n",
       "<td>0.2445826</td>\n",
       "<td>0.0305914</td>\n",
       "<td>0.9735477</td>\n",
       "<td>-69.4081184</td>\n",
       "<td>39.0789139</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999950</td>\n",
       "<td>0.0658875</td>\n",
       "<td>0.1750826</td>\n",
       "<td>1.2388274</td>\n",
       "<td>0.0307898</td>\n",
       "<td>0.2178587</td>\n",
       "<td>0.0175080</td>\n",
       "<td>0.9910557</td>\n",
       "<td>-82.4917380</td>\n",
       "<td>23.8827413</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999933</td>\n",
       "<td>0.0501151</td>\n",
       "<td>0.0765986</td>\n",
       "<td>1.1096921</td>\n",
       "<td>0.0134705</td>\n",
       "<td>0.1951492</td>\n",
       "<td>0.0076597</td>\n",
       "<td>0.9987154</td>\n",
       "<td>-92.3401354</td>\n",
       "<td>10.9692084</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0069006</td>\n",
       "<td>0.0128447</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0022588</td>\n",
       "<td>0.1758588</td>\n",
       "<td>0.0012846</td>\n",
       "<td>1.0</td>\n",
       "<td>-98.7155339</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift       cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  ---------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100065                   0.72554            5.68638    5.68638            1                1                           0.0569009       0.0569009                  468.638   468.638\n",
       "    2        0.0200047                   0.63094            5.68162    5.684              0.999163         0.999582                    0.0568057       0.113707                   468.162   468.4\n",
       "    3        0.0300028                   0.559751           5.5579     5.64198            0.977406         0.992192                    0.0555688       0.169275                   455.79    464.198\n",
       "    4        0.040001                    0.50424            5.47225    5.59955            0.962343         0.984731                    0.0547124       0.223988                   447.225   459.955\n",
       "    5        0.0500075                   0.459543           5.20617    5.52084            0.915552         0.970888                    0.0520957       0.276084                   420.617   452.084\n",
       "    6        0.100007                    0.365678           3.88512    4.70305            0.683233         0.827073                    0.194253        0.470336                   288.512   370.305\n",
       "    7        0.150006                    0.315675           2.2951     3.90045            0.403614         0.685928                    0.114753        0.58509                    129.51    290.045\n",
       "    8        0.200005                    0.274731           1.72513    3.35664            0.30338          0.590295                    0.0862553       0.671345                   72.5135   235.664\n",
       "    9        0.300003                    0.213902           1.15088    2.62141            0.202393         0.460998                    0.115086        0.786431                   15.0883   162.141\n",
       "    10       0.400002                    0.166599           0.730304   2.14864            0.12843          0.377858                    0.0730292       0.85946                    -26.9696  114.864\n",
       "    11       0.5                         0.124722           0.440085   1.80694            0.0773929        0.317766                    0.0440078       0.903468                   -55.9915  80.6937\n",
       "    12       0.599998                    0.0939096          0.394887   1.5716             0.0694444        0.276379                    0.0394881       0.942956                   -60.5113  57.1598\n",
       "    13       0.699997                    0.0771937          0.305919   1.39079            0.0537985        0.244583                    0.0305914       0.973548                   -69.4081  39.0789\n",
       "    14       0.799995                    0.0658875          0.175083   1.23883            0.0307898        0.217859                    0.017508        0.991056                   -82.4917  23.8827\n",
       "    15       0.899993                    0.0501151          0.0765986  1.10969            0.0134705        0.195149                    0.00765974      0.998715                   -92.3401  10.9692\n",
       "    16       1                           0.00690056         0.0128447  1                  0.00225885       0.175859                    0.00128455      1                          -98.7155  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on validation data. **\n",
      "\n",
      "MSE: 0.12483107919936037\n",
      "RMSE: 0.3533144197444542\n",
      "LogLoss: 0.3979140718405067\n",
      "Mean Per-Class Error: 0.3009806315100858\n",
      "AUC: 0.7665512771103373\n",
      "Gini: 0.5331025542206747\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.22745429493160918: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>32454.0</td>\n",
       "<td>9733.0</td>\n",
       "<td>0.2307</td>\n",
       "<td> (9733.0/42187.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>3504.0</td>\n",
       "<td>5533.0</td>\n",
       "<td>0.3877</td>\n",
       "<td> (3504.0/9037.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>35958.0</td>\n",
       "<td>15266.0</td>\n",
       "<td>0.2584</td>\n",
       "<td> (13237.0/51224.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  -----------------\n",
       "0      32454  9733   0.2307   (9733.0/42187.0)\n",
       "1      3504   5533   0.3877   (3504.0/9037.0)\n",
       "Total  35958  15266  0.2584   (13237.0/51224.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2274543</td>\n",
       "<td>0.4553347</td>\n",
       "<td>216.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1142319</td>\n",
       "<td>0.6001856</td>\n",
       "<td>302.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3154891</td>\n",
       "<td>0.4207902</td>\n",
       "<td>157.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4531076</td>\n",
       "<td>0.8305677</td>\n",
       "<td>88.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.9150186</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0127408</td>\n",
       "<td>1.0</td>\n",
       "<td>397.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9150186</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2274543</td>\n",
       "<td>0.3179745</td>\n",
       "<td>216.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1924641</td>\n",
       "<td>0.6985801</td>\n",
       "<td>241.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1807626</td>\n",
       "<td>0.6990194</td>\n",
       "<td>250.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.227454     0.455335  216\n",
       "max f2                       0.114232     0.600186  302\n",
       "max f0point5                 0.315489     0.42079   157\n",
       "max accuracy                 0.453108     0.830568  88\n",
       "max precision                0.915019     1         0\n",
       "max recall                   0.0127408    1         397\n",
       "max specificity              0.915019     1         0\n",
       "max absolute_mcc             0.227454     0.317975  216\n",
       "max min_per_class_accuracy   0.192464     0.69858   241\n",
       "max mean_per_class_accuracy  0.180763     0.699019  250"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,64 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100148</td>\n",
       "<td>0.6075336</td>\n",
       "<td>4.1766073</td>\n",
       "<td>4.1766073</td>\n",
       "<td>0.7368421</td>\n",
       "<td>0.7368421</td>\n",
       "<td>0.0418280</td>\n",
       "<td>0.0418280</td>\n",
       "<td>317.6607281</td>\n",
       "<td>317.6607281</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200102</td>\n",
       "<td>0.5192058</td>\n",
       "<td>3.0998257</td>\n",
       "<td>3.6387418</td>\n",
       "<td>0.546875</td>\n",
       "<td>0.6419512</td>\n",
       "<td>0.0309837</td>\n",
       "<td>0.0728118</td>\n",
       "<td>209.9825716</td>\n",
       "<td>263.8741758</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300055</td>\n",
       "<td>0.4681068</td>\n",
       "<td>3.1773214</td>\n",
       "<td>3.4850350</td>\n",
       "<td>0.5605469</td>\n",
       "<td>0.6148341</td>\n",
       "<td>0.0317583</td>\n",
       "<td>0.1045701</td>\n",
       "<td>217.7321359</td>\n",
       "<td>248.5035028</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400008</td>\n",
       "<td>0.4329442</td>\n",
       "<td>2.5462854</td>\n",
       "<td>3.2504622</td>\n",
       "<td>0.4492188</td>\n",
       "<td>0.5734505</td>\n",
       "<td>0.0254509</td>\n",
       "<td>0.1300210</td>\n",
       "<td>154.6285410</td>\n",
       "<td>225.0462161</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500156</td>\n",
       "<td>0.4125622</td>\n",
       "<td>2.5192234</td>\n",
       "<td>3.1040432</td>\n",
       "<td>0.4444444</td>\n",
       "<td>0.5476190</td>\n",
       "<td>0.0252296</td>\n",
       "<td>0.1552506</td>\n",
       "<td>151.9223439</td>\n",
       "<td>210.4043166</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000117</td>\n",
       "<td>0.3586610</td>\n",
       "<td>2.3062551</td>\n",
       "<td>2.7052270</td>\n",
       "<td>0.4068723</td>\n",
       "<td>0.4772594</td>\n",
       "<td>0.1153038</td>\n",
       "<td>0.2705544</td>\n",
       "<td>130.6255117</td>\n",
       "<td>170.5227005</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500078</td>\n",
       "<td>0.3166723</td>\n",
       "<td>1.9919670</td>\n",
       "<td>2.4675046</td>\n",
       "<td>0.3514252</td>\n",
       "<td>0.4353201</td>\n",
       "<td>0.0995906</td>\n",
       "<td>0.3701450</td>\n",
       "<td>99.1966991</td>\n",
       "<td>146.7504608</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000039</td>\n",
       "<td>0.2810350</td>\n",
       "<td>1.8171166</td>\n",
       "<td>2.3049235</td>\n",
       "<td>0.3205779</td>\n",
       "<td>0.4066374</td>\n",
       "<td>0.0908487</td>\n",
       "<td>0.4609937</td>\n",
       "<td>81.7116555</td>\n",
       "<td>130.4923466</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.2999961</td>\n",
       "<td>0.2257051</td>\n",
       "<td>1.5327079</td>\n",
       "<td>2.0475350</td>\n",
       "<td>0.2704022</td>\n",
       "<td>0.3612286</td>\n",
       "<td>0.1532588</td>\n",
       "<td>0.6142525</td>\n",
       "<td>53.2707935</td>\n",
       "<td>104.7535040</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000078</td>\n",
       "<td>0.1787912</td>\n",
       "<td>1.1318803</td>\n",
       "<td>1.8185990</td>\n",
       "<td>0.1996877</td>\n",
       "<td>0.3208394</td>\n",
       "<td>0.1132013</td>\n",
       "<td>0.7274538</td>\n",
       "<td>13.1880256</td>\n",
       "<td>81.8599000</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1373174</td>\n",
       "<td>0.9074516</td>\n",
       "<td>1.6363838</td>\n",
       "<td>0.1600937</td>\n",
       "<td>0.2886928</td>\n",
       "<td>0.0907381</td>\n",
       "<td>0.8181919</td>\n",
       "<td>-9.2548371</td>\n",
       "<td>63.6383756</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999922</td>\n",
       "<td>0.0997335</td>\n",
       "<td>0.6650956</td>\n",
       "<td>1.4745129</td>\n",
       "<td>0.1173370</td>\n",
       "<td>0.2601354</td>\n",
       "<td>0.0665044</td>\n",
       "<td>0.8846962</td>\n",
       "<td>-33.4904355</td>\n",
       "<td>47.4512938</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.7000039</td>\n",
       "<td>0.0797965</td>\n",
       "<td>0.4746595</td>\n",
       "<td>1.3316608</td>\n",
       "<td>0.0837400</td>\n",
       "<td>0.2349332</td>\n",
       "<td>0.0474715</td>\n",
       "<td>0.9321678</td>\n",
       "<td>-52.5340538</td>\n",
       "<td>33.1660793</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999961</td>\n",
       "<td>0.0675917</td>\n",
       "<td>0.3574474</td>\n",
       "<td>1.2098930</td>\n",
       "<td>0.0630613</td>\n",
       "<td>0.2134508</td>\n",
       "<td>0.0357419</td>\n",
       "<td>0.9679097</td>\n",
       "<td>-64.2552590</td>\n",
       "<td>20.9893036</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999883</td>\n",
       "<td>0.0517834</td>\n",
       "<td>0.2202230</td>\n",
       "<td>1.0999369</td>\n",
       "<td>0.0388520</td>\n",
       "<td>0.1940522</td>\n",
       "<td>0.0220206</td>\n",
       "<td>0.9899303</td>\n",
       "<td>-77.9776983</td>\n",
       "<td>9.9936856</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0070596</td>\n",
       "<td>0.1006853</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0177630</td>\n",
       "<td>0.1764212</td>\n",
       "<td>0.0100697</td>\n",
       "<td>1.0</td>\n",
       "<td>-89.9314660</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift      cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  --------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100148                   0.607534           4.17661   4.17661            0.736842         0.736842                    0.041828        0.041828                   317.661   317.661\n",
       "    2        0.0200102                   0.519206           3.09983   3.63874            0.546875         0.641951                    0.0309837       0.0728118                  209.983   263.874\n",
       "    3        0.0300055                   0.468107           3.17732   3.48504            0.560547         0.614834                    0.0317583       0.10457                    217.732   248.504\n",
       "    4        0.0400008                   0.432944           2.54629   3.25046            0.449219         0.57345                     0.0254509       0.130021                   154.629   225.046\n",
       "    5        0.0500156                   0.412562           2.51922   3.10404            0.444444         0.547619                    0.0252296       0.155251                   151.922   210.404\n",
       "    6        0.100012                    0.358661           2.30626   2.70523            0.406872         0.477259                    0.115304        0.270554                   130.626   170.523\n",
       "    7        0.150008                    0.316672           1.99197   2.4675             0.351425         0.43532                     0.0995906       0.370145                   99.1967   146.75\n",
       "    8        0.200004                    0.281035           1.81712   2.30492            0.320578         0.406637                    0.0908487       0.460994                   81.7117   130.492\n",
       "    9        0.299996                    0.225705           1.53271   2.04754            0.270402         0.361229                    0.153259        0.614253                   53.2708   104.754\n",
       "    10       0.400008                    0.178791           1.13188   1.8186             0.199688         0.320839                    0.113201        0.727454                   13.188    81.8599\n",
       "    11       0.5                         0.137317           0.907452  1.63638            0.160094         0.288693                    0.0907381       0.818192                   -9.25484  63.6384\n",
       "    12       0.599992                    0.0997335          0.665096  1.47451            0.117337         0.260135                    0.0665044       0.884696                   -33.4904  47.4513\n",
       "    13       0.700004                    0.0797965          0.474659  1.33166            0.08374          0.234933                    0.0474715       0.932168                   -52.5341  33.1661\n",
       "    14       0.799996                    0.0675917          0.357447  1.20989            0.0630613        0.213451                    0.0357419       0.96791                    -64.2553  20.9893\n",
       "    15       0.899988                    0.0517834          0.220223  1.09994            0.038852         0.194052                    0.0220206       0.98993                    -77.9777  9.99369\n",
       "    16       1                           0.00705962         0.100685  1                  0.017763         0.176421                    0.0100697       1                          -89.9315  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "ModelMetricsBinomial: drf\n",
      "** Reported on cross-validation data. **\n",
      "\n",
      "MSE: 0.12509233392808441\n",
      "RMSE: 0.353683946381631\n",
      "LogLoss: 0.3995105250446784\n",
      "Mean Per-Class Error: 0.30391724692412003\n",
      "AUC: 0.7612882132260508\n",
      "Gini: 0.5225764264521016\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.22922815900875956: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>76269.0</td>\n",
       "<td>22234.0</td>\n",
       "<td>0.2257</td>\n",
       "<td> (22234.0/98503.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>8456.0</td>\n",
       "<td>12563.0</td>\n",
       "<td>0.4023</td>\n",
       "<td> (8456.0/21019.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>84725.0</td>\n",
       "<td>34797.0</td>\n",
       "<td>0.2568</td>\n",
       "<td> (30690.0/119522.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  ------------------\n",
       "0      76269  22234  0.2257   (22234.0/98503.0)\n",
       "1      8456   12563  0.4023   (8456.0/21019.0)\n",
       "Total  84725  34797  0.2568   (30690.0/119522.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.2292282</td>\n",
       "<td>0.4501577</td>\n",
       "<td>217.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1185492</td>\n",
       "<td>0.5956491</td>\n",
       "<td>303.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.3130699</td>\n",
       "<td>0.4178212</td>\n",
       "<td>163.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.4647717</td>\n",
       "<td>0.8311692</td>\n",
       "<td>88.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.7806692</td>\n",
       "<td>0.8289474</td>\n",
       "<td>17.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0132798</td>\n",
       "<td>1.0</td>\n",
       "<td>397.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9528907</td>\n",
       "<td>0.9999898</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.2292282</td>\n",
       "<td>0.3117250</td>\n",
       "<td>217.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1900628</td>\n",
       "<td>0.6933727</td>\n",
       "<td>247.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1841789</td>\n",
       "<td>0.6960828</td>\n",
       "<td>251.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.229228     0.450158  217\n",
       "max f2                       0.118549     0.595649  303\n",
       "max f0point5                 0.31307      0.417821  163\n",
       "max accuracy                 0.464772     0.831169  88\n",
       "max precision                0.780669     0.828947  17\n",
       "max recall                   0.0132798    1         397\n",
       "max specificity              0.952891     0.99999   0\n",
       "max absolute_mcc             0.229228     0.311725  217\n",
       "max min_per_class_accuracy   0.190063     0.693373  247\n",
       "max mean_per_class_accuracy  0.184179     0.696083  251"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,59 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100065</td>\n",
       "<td>0.6149464</td>\n",
       "<td>4.0983768</td>\n",
       "<td>4.0983768</td>\n",
       "<td>0.7207358</td>\n",
       "<td>0.7207358</td>\n",
       "<td>0.0410105</td>\n",
       "<td>0.0410105</td>\n",
       "<td>309.8376831</td>\n",
       "<td>309.8376831</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200047</td>\n",
       "<td>0.5234847</td>\n",
       "<td>3.3309333</td>\n",
       "<td>3.7148156</td>\n",
       "<td>0.5857741</td>\n",
       "<td>0.6532831</td>\n",
       "<td>0.0333032</td>\n",
       "<td>0.0743137</td>\n",
       "<td>233.0933300</td>\n",
       "<td>271.4815551</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300028</td>\n",
       "<td>0.4697528</td>\n",
       "<td>3.0834925</td>\n",
       "<td>3.5044332</td>\n",
       "<td>0.5422594</td>\n",
       "<td>0.6162856</td>\n",
       "<td>0.0308292</td>\n",
       "<td>0.1051430</td>\n",
       "<td>208.3492540</td>\n",
       "<td>250.4433232</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400010</td>\n",
       "<td>0.4362686</td>\n",
       "<td>2.6266788</td>\n",
       "<td>3.2850405</td>\n",
       "<td>0.4619247</td>\n",
       "<td>0.5777034</td>\n",
       "<td>0.0262620</td>\n",
       "<td>0.1314049</td>\n",
       "<td>162.6678831</td>\n",
       "<td>228.5040530</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500075</td>\n",
       "<td>0.4152627</td>\n",
       "<td>2.4105302</td>\n",
       "<td>3.1100507</td>\n",
       "<td>0.4239130</td>\n",
       "<td>0.5469299</td>\n",
       "<td>0.0241210</td>\n",
       "<td>0.1555260</td>\n",
       "<td>141.0530224</td>\n",
       "<td>211.0050681</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000067</td>\n",
       "<td>0.3596503</td>\n",
       "<td>2.2494310</td>\n",
       "<td>2.6797769</td>\n",
       "<td>0.3955823</td>\n",
       "<td>0.4712624</td>\n",
       "<td>0.1124697</td>\n",
       "<td>0.2679956</td>\n",
       "<td>124.9431046</td>\n",
       "<td>167.9776864</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500059</td>\n",
       "<td>0.3168781</td>\n",
       "<td>1.9991771</td>\n",
       "<td>2.4529229</td>\n",
       "<td>0.3515730</td>\n",
       "<td>0.4313682</td>\n",
       "<td>0.0999572</td>\n",
       "<td>0.3679528</td>\n",
       "<td>99.9177085</td>\n",
       "<td>145.2922924</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000050</td>\n",
       "<td>0.2815969</td>\n",
       "<td>1.8050637</td>\n",
       "<td>2.2909649</td>\n",
       "<td>0.3174364</td>\n",
       "<td>0.4028864</td>\n",
       "<td>0.0902517</td>\n",
       "<td>0.4582045</td>\n",
       "<td>80.5063746</td>\n",
       "<td>129.0964905</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.3000033</td>\n",
       "<td>0.2240506</td>\n",
       "<td>1.4977176</td>\n",
       "<td>2.0265565</td>\n",
       "<td>0.2633869</td>\n",
       "<td>0.3563879</td>\n",
       "<td>0.1497693</td>\n",
       "<td>0.6079737</td>\n",
       "<td>49.7717626</td>\n",
       "<td>102.6556519</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000017</td>\n",
       "<td>0.1770853</td>\n",
       "<td>1.1456493</td>\n",
       "<td>1.8063343</td>\n",
       "<td>0.2014726</td>\n",
       "<td>0.3176599</td>\n",
       "<td>0.1145630</td>\n",
       "<td>0.7225368</td>\n",
       "<td>14.5649315</td>\n",
       "<td>80.6334325</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1350422</td>\n",
       "<td>0.8944438</td>\n",
       "<td>1.6239593</td>\n",
       "<td>0.1572959</td>\n",
       "<td>0.2855876</td>\n",
       "<td>0.0894429</td>\n",
       "<td>0.8119796</td>\n",
       "<td>-10.5556183</td>\n",
       "<td>62.3959275</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999983</td>\n",
       "<td>0.0997045</td>\n",
       "<td>0.6584629</td>\n",
       "<td>1.4630455</td>\n",
       "<td>0.1157965</td>\n",
       "<td>0.2572895</td>\n",
       "<td>0.0658452</td>\n",
       "<td>0.8778248</td>\n",
       "<td>-34.1537105</td>\n",
       "<td>46.3045456</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.6999967</td>\n",
       "<td>0.0800967</td>\n",
       "<td>0.4829045</td>\n",
       "<td>1.3230270</td>\n",
       "<td>0.0849230</td>\n",
       "<td>0.2326660</td>\n",
       "<td>0.0482896</td>\n",
       "<td>0.9261145</td>\n",
       "<td>-51.7095492</td>\n",
       "<td>32.3026994</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999950</td>\n",
       "<td>0.0676811</td>\n",
       "<td>0.3406499</td>\n",
       "<td>1.2002311</td>\n",
       "<td>0.0599063</td>\n",
       "<td>0.2110713</td>\n",
       "<td>0.0340644</td>\n",
       "<td>0.9601789</td>\n",
       "<td>-65.9350121</td>\n",
       "<td>20.0231139</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999933</td>\n",
       "<td>0.0520891</td>\n",
       "<td>0.2730908</td>\n",
       "<td>1.0972165</td>\n",
       "<td>0.0480254</td>\n",
       "<td>0.1929552</td>\n",
       "<td>0.0273086</td>\n",
       "<td>0.9874875</td>\n",
       "<td>-72.6909175</td>\n",
       "<td>9.7216506</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0059183</td>\n",
       "<td>0.1251165</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0220028</td>\n",
       "<td>0.1758588</td>\n",
       "<td>0.0125125</td>\n",
       "<td>1.0</td>\n",
       "<td>-87.4883487</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift      cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  --------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100065                   0.614946           4.09838   4.09838            0.720736         0.720736                    0.0410105       0.0410105                  309.838   309.838\n",
       "    2        0.0200047                   0.523485           3.33093   3.71482            0.585774         0.653283                    0.0333032       0.0743137                  233.093   271.482\n",
       "    3        0.0300028                   0.469753           3.08349   3.50443            0.542259         0.616286                    0.0308292       0.105143                   208.349   250.443\n",
       "    4        0.040001                    0.436269           2.62668   3.28504            0.461925         0.577703                    0.026262        0.131405                   162.668   228.504\n",
       "    5        0.0500075                   0.415263           2.41053   3.11005            0.423913         0.54693                     0.024121        0.155526                   141.053   211.005\n",
       "    6        0.100007                    0.35965            2.24943   2.67978            0.395582         0.471262                    0.11247         0.267996                   124.943   167.978\n",
       "    7        0.150006                    0.316878           1.99918   2.45292            0.351573         0.431368                    0.0999572       0.367953                   99.9177   145.292\n",
       "    8        0.200005                    0.281597           1.80506   2.29096            0.317436         0.402886                    0.0902517       0.458204                   80.5064   129.096\n",
       "    9        0.300003                    0.224051           1.49772   2.02656            0.263387         0.356388                    0.149769        0.607974                   49.7718   102.656\n",
       "    10       0.400002                    0.177085           1.14565   1.80633            0.201473         0.31766                     0.114563        0.722537                   14.5649   80.6334\n",
       "    11       0.5                         0.135042           0.894444  1.62396            0.157296         0.285588                    0.0894429       0.81198                    -10.5556  62.3959\n",
       "    12       0.599998                    0.0997045          0.658463  1.46305            0.115797         0.257289                    0.0658452       0.877825                   -34.1537  46.3045\n",
       "    13       0.699997                    0.0800967          0.482905  1.32303            0.084923         0.232666                    0.0482896       0.926114                   -51.7095  32.3027\n",
       "    14       0.799995                    0.0676811          0.34065   1.20023            0.0599063        0.211071                    0.0340644       0.960179                   -65.935   20.0231\n",
       "    15       0.899993                    0.0520891          0.273091  1.09722            0.0480254        0.192955                    0.0273086       0.987488                   -72.6909  9.72165\n",
       "    16       1                           0.00591831         0.125117  1                  0.0220028        0.175859                    0.0125125       1                          -87.4883  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Cross-Validation Metrics Summary: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>mean</b></td>\n",
       "<td><b>sd</b></td>\n",
       "<td><b>cv_1_valid</b></td>\n",
       "<td><b>cv_2_valid</b></td>\n",
       "<td><b>cv_3_valid</b></td>\n",
       "<td><b>cv_4_valid</b></td>\n",
       "<td><b>cv_5_valid</b></td></tr>\n",
       "<tr><td>accuracy</td>\n",
       "<td>0.7388554</td>\n",
       "<td>0.0046259</td>\n",
       "<td>0.7479348</td>\n",
       "<td>0.7384176</td>\n",
       "<td>0.7395335</td>\n",
       "<td>0.7408087</td>\n",
       "<td>0.7275822</td></tr>\n",
       "<tr><td>auc</td>\n",
       "<td>0.7613639</td>\n",
       "<td>0.0018956</td>\n",
       "<td>0.760337</td>\n",
       "<td>0.7609469</td>\n",
       "<td>0.7631720</td>\n",
       "<td>0.7572213</td>\n",
       "<td>0.7651421</td></tr>\n",
       "<tr><td>err</td>\n",
       "<td>0.2611446</td>\n",
       "<td>0.0046259</td>\n",
       "<td>0.2520652</td>\n",
       "<td>0.2615824</td>\n",
       "<td>0.2604665</td>\n",
       "<td>0.2591912</td>\n",
       "<td>0.2724178</td></tr>\n",
       "<tr><td>err_count</td>\n",
       "<td>6243.0</td>\n",
       "<td>125.77997</td>\n",
       "<td>6011.0</td>\n",
       "<td>6222.0</td>\n",
       "<td>6209.0</td>\n",
       "<td>6211.0</td>\n",
       "<td>6562.0</td></tr>\n",
       "<tr><td>f0point5</td>\n",
       "<td>0.3903328</td>\n",
       "<td>0.0028290</td>\n",
       "<td>0.3924213</td>\n",
       "<td>0.3944569</td>\n",
       "<td>0.3935865</td>\n",
       "<td>0.3868779</td>\n",
       "<td>0.3843213</td></tr>\n",
       "<tr><td>f1</td>\n",
       "<td>0.4513294</td>\n",
       "<td>0.0029902</td>\n",
       "<td>0.4484815</td>\n",
       "<td>0.4548800</td>\n",
       "<td>0.4559713</td>\n",
       "<td>0.4446034</td>\n",
       "<td>0.4527106</td></tr>\n",
       "<tr><td>f2</td>\n",
       "<td>0.5351067</td>\n",
       "<td>0.0076897</td>\n",
       "<td>0.5232284</td>\n",
       "<td>0.5371627</td>\n",
       "<td>0.5418575</td>\n",
       "<td>0.5225763</td>\n",
       "<td>0.5507082</td></tr>\n",
       "<tr><td>lift_top_group</td>\n",
       "<td>4.0911126</td>\n",
       "<td>0.1202592</td>\n",
       "<td>4.3016148</td>\n",
       "<td>3.8565536</td>\n",
       "<td>3.9430668</td>\n",
       "<td>4.1117187</td>\n",
       "<td>4.24261</td></tr>\n",
       "<tr><td>logloss</td>\n",
       "<td>0.3995180</td>\n",
       "<td>0.0019004</td>\n",
       "<td>0.397185</td>\n",
       "<td>0.4040511</td>\n",
       "<td>0.3994198</td>\n",
       "<td>0.4004555</td>\n",
       "<td>0.3964789</td></tr>\n",
       "<tr><td>max_per_class_error</td>\n",
       "<td>0.3891047</td>\n",
       "<td>0.0141681</td>\n",
       "<td>0.411368</td>\n",
       "<td>0.3891765</td>\n",
       "<td>0.3803287</td>\n",
       "<td>0.4082362</td>\n",
       "<td>0.3564145</td></tr>\n",
       "<tr><td>mcc</td>\n",
       "<td>0.3133101</td>\n",
       "<td>0.0034555</td>\n",
       "<td>0.3116242</td>\n",
       "<td>0.3147986</td>\n",
       "<td>0.3191160</td>\n",
       "<td>0.3048089</td>\n",
       "<td>0.316203</td></tr>\n",
       "<tr><td>mean_per_class_accuracy</td>\n",
       "<td>0.6885231</td>\n",
       "<td>0.0032191</td>\n",
       "<td>0.6850750</td>\n",
       "<td>0.6884994</td>\n",
       "<td>0.6924162</td>\n",
       "<td>0.6821282</td>\n",
       "<td>0.6944967</td></tr>\n",
       "<tr><td>mean_per_class_error</td>\n",
       "<td>0.3114769</td>\n",
       "<td>0.0032191</td>\n",
       "<td>0.3149249</td>\n",
       "<td>0.3115006</td>\n",
       "<td>0.3075837</td>\n",
       "<td>0.3178718</td>\n",
       "<td>0.3055033</td></tr>\n",
       "<tr><td>mse</td>\n",
       "<td>0.1250953</td>\n",
       "<td>0.0007560</td>\n",
       "<td>0.1240488</td>\n",
       "<td>0.1269616</td>\n",
       "<td>0.1251834</td>\n",
       "<td>0.1252401</td>\n",
       "<td>0.1240425</td></tr>\n",
       "<tr><td>precision</td>\n",
       "<td>0.3581012</td>\n",
       "<td>0.0035517</td>\n",
       "<td>0.3622351</td>\n",
       "<td>0.3623674</td>\n",
       "<td>0.3606876</td>\n",
       "<td>0.3560585</td>\n",
       "<td>0.3491573</td></tr>\n",
       "<tr><td>r2</td>\n",
       "<td>0.1368789</td>\n",
       "<td>0.0017904</td>\n",
       "<td>0.1373262</td>\n",
       "<td>0.1348513</td>\n",
       "<td>0.1373767</td>\n",
       "<td>0.1337520</td>\n",
       "<td>0.1410883</td></tr>\n",
       "<tr><td>recall</td>\n",
       "<td>0.6108952</td>\n",
       "<td>0.0141681</td>\n",
       "<td>0.588632</td>\n",
       "<td>0.6108235</td>\n",
       "<td>0.6196713</td>\n",
       "<td>0.5917638</td>\n",
       "<td>0.6435855</td></tr>\n",
       "<tr><td>rmse</td>\n",
       "<td>0.3536849</td>\n",
       "<td>0.0010672</td>\n",
       "<td>0.3522056</td>\n",
       "<td>0.3563168</td>\n",
       "<td>0.3538127</td>\n",
       "<td>0.3538928</td>\n",
       "<td>0.3521966</td></tr>\n",
       "<tr><td>specificity</td>\n",
       "<td>0.766151</td>\n",
       "<td>0.0084120</td>\n",
       "<td>0.7815182</td>\n",
       "<td>0.7661753</td>\n",
       "<td>0.7651612</td>\n",
       "<td>0.7724927</td>\n",
       "<td>0.7454079</td></tr></table></div>"
      ],
      "text/plain": [
       "                         mean      sd           cv_1_valid    cv_2_valid    cv_3_valid    cv_4_valid    cv_5_valid\n",
       "-----------------------  --------  -----------  ------------  ------------  ------------  ------------  ------------\n",
       "accuracy                 0.738855  0.00462587   0.747935      0.738418      0.739534      0.740809      0.727582\n",
       "auc                      0.761364  0.00189564   0.760337      0.760947      0.763172      0.757221      0.765142\n",
       "err                      0.261145  0.00462587   0.252065      0.261582      0.260466      0.259191      0.272418\n",
       "err_count                6243      125.78       6011          6222          6209          6211          6562\n",
       "f0point5                 0.390333  0.00282898   0.392421      0.394457      0.393586      0.386878      0.384321\n",
       "f1                       0.451329  0.00299016   0.448481      0.45488       0.455971      0.444603      0.452711\n",
       "f2                       0.535107  0.00768968   0.523228      0.537163      0.541858      0.522576      0.550708\n",
       "lift_top_group           4.09111   0.120259     4.30161       3.85655       3.94307       4.11172       4.24261\n",
       "logloss                  0.399518  0.00190044   0.397185      0.404051      0.39942       0.400455      0.396479\n",
       "max_per_class_error      0.389105  0.0141681    0.411368      0.389176      0.380329      0.408236      0.356415\n",
       "mcc                      0.31331   0.00345552   0.311624      0.314799      0.319116      0.304809      0.316203\n",
       "mean_per_class_accuracy  0.688523  0.00321906   0.685075      0.688499      0.692416      0.682128      0.694497\n",
       "mean_per_class_error     0.311477  0.00321906   0.314925      0.311501      0.307584      0.317872      0.305503\n",
       "mse                      0.125095  0.000756017  0.124049      0.126962      0.125183      0.12524       0.124042\n",
       "precision                0.358101  0.00355168   0.362235      0.362367      0.360688      0.356058      0.349157\n",
       "r2                       0.136879  0.00179039   0.137326      0.134851      0.137377      0.133752      0.141088\n",
       "recall                   0.610895  0.0141681    0.588632      0.610823      0.619671      0.591764      0.643586\n",
       "rmse                     0.353685  0.00106722   0.352206      0.356317      0.353813      0.353893      0.352197\n",
       "specificity              0.766151  0.00841203   0.781518      0.766175      0.765161      0.772493      0.745408"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scoring History: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>timestamp</b></td>\n",
       "<td><b>duration</b></td>\n",
       "<td><b>number_of_trees</b></td>\n",
       "<td><b>training_rmse</b></td>\n",
       "<td><b>training_logloss</b></td>\n",
       "<td><b>training_auc</b></td>\n",
       "<td><b>training_lift</b></td>\n",
       "<td><b>training_classification_error</b></td>\n",
       "<td><b>validation_rmse</b></td>\n",
       "<td><b>validation_logloss</b></td>\n",
       "<td><b>validation_auc</b></td>\n",
       "<td><b>validation_lift</b></td>\n",
       "<td><b>validation_classification_error</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-13 09:35:47</td>\n",
       "<td>10:11:54.916</td>\n",
       "<td>0.0</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td>\n",
       "<td>nan</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-13 09:35:47</td>\n",
       "<td>10:11:55.554</td>\n",
       "<td>1.0</td>\n",
       "<td>0.3914979</td>\n",
       "<td>1.7137480</td>\n",
       "<td>0.6606974</td>\n",
       "<td>4.1345559</td>\n",
       "<td>0.2917141</td>\n",
       "<td>0.3883276</td>\n",
       "<td>1.6265088</td>\n",
       "<td>0.6701004</td>\n",
       "<td>2.3487436</td>\n",
       "<td>0.2998594</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-13 09:35:48</td>\n",
       "<td>10:11:56.006</td>\n",
       "<td>2.0</td>\n",
       "<td>0.3877207</td>\n",
       "<td>1.4859533</td>\n",
       "<td>0.6672446</td>\n",
       "<td>5.3587687</td>\n",
       "<td>0.2949230</td>\n",
       "<td>0.3712470</td>\n",
       "<td>0.6731222</td>\n",
       "<td>0.7077018</td>\n",
       "<td>3.1269308</td>\n",
       "<td>0.2948813</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-13 09:35:49</td>\n",
       "<td>10:11:57.023</td>\n",
       "<td>3.0</td>\n",
       "<td>0.3831936</td>\n",
       "<td>1.2484785</td>\n",
       "<td>0.6797248</td>\n",
       "<td>5.5248611</td>\n",
       "<td>0.2923736</td>\n",
       "<td>0.3658625</td>\n",
       "<td>0.4866217</td>\n",
       "<td>0.7227650</td>\n",
       "<td>3.5357522</td>\n",
       "<td>0.2755349</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-13 09:35:50</td>\n",
       "<td>10:11:58.179</td>\n",
       "<td>4.0</td>\n",
       "<td>0.3808052</td>\n",
       "<td>1.1266968</td>\n",
       "<td>0.6838215</td>\n",
       "<td>5.5865345</td>\n",
       "<td>0.3144572</td>\n",
       "<td>0.3626566</td>\n",
       "<td>0.4353914</td>\n",
       "<td>0.7327566</td>\n",
       "<td>3.6462445</td>\n",
       "<td>0.2813915</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-13 09:36:00</td>\n",
       "<td>10:12:08.141</td>\n",
       "<td>39.0</td>\n",
       "<td>0.3564109</td>\n",
       "<td>0.4053380</td>\n",
       "<td>0.7503262</td>\n",
       "<td>5.6816245</td>\n",
       "<td>0.2764512</td>\n",
       "<td>0.3540971</td>\n",
       "<td>0.3996028</td>\n",
       "<td>0.7626536</td>\n",
       "<td>4.0329673</td>\n",
       "<td>0.2597610</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-13 09:36:41</td>\n",
       "<td>10:12:49.269</td>\n",
       "<td>184.0</td>\n",
       "<td>0.3541230</td>\n",
       "<td>0.4003132</td>\n",
       "<td>0.7597469</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2724854</td>\n",
       "<td>0.3534297</td>\n",
       "<td>0.3981844</td>\n",
       "<td>0.7661178</td>\n",
       "<td>4.1213612</td>\n",
       "<td>0.2517960</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2017-07-13 09:39:38</td>\n",
       "<td>10:15:45.872</td>\n",
       "<td>800.0</td>\n",
       "<td>0.3535750</td>\n",
       "<td>0.3991890</td>\n",
       "<td>0.7619702</td>\n",
       "<td>5.6863790</td>\n",
       "<td>0.2591908</td>\n",
       "<td>0.3533144</td>\n",
       "<td>0.3979141</td>\n",
       "<td>0.7665513</td>\n",
       "<td>4.1766073</td>\n",
       "<td>0.2584140</td></tr></table></div>"
      ],
      "text/plain": [
       "    timestamp            duration      number_of_trees    training_rmse    training_logloss    training_auc    training_lift    training_classification_error    validation_rmse    validation_logloss    validation_auc    validation_lift    validation_classification_error\n",
       "--  -------------------  ------------  -----------------  ---------------  ------------------  --------------  ---------------  -------------------------------  -----------------  --------------------  ----------------  -----------------  ---------------------------------\n",
       "    2017-07-13 09:35:47  10:11:54.916  0                  nan              nan                 nan             nan              nan                              nan                nan                   nan               nan                nan\n",
       "    2017-07-13 09:35:47  10:11:55.554  1                  0.391498         1.71375             0.660697        4.13456          0.291714                         0.388328           1.62651               0.6701            2.34874            0.299859\n",
       "    2017-07-13 09:35:48  10:11:56.006  2                  0.387721         1.48595             0.667245        5.35877          0.294923                         0.371247           0.673122              0.707702          3.12693            0.294881\n",
       "    2017-07-13 09:35:49  10:11:57.023  3                  0.383194         1.24848             0.679725        5.52486          0.292374                         0.365862           0.486622              0.722765          3.53575            0.275535\n",
       "    2017-07-13 09:35:50  10:11:58.179  4                  0.380805         1.1267              0.683821        5.58653          0.314457                         0.362657           0.435391              0.732757          3.64624            0.281392\n",
       "    2017-07-13 09:36:00  10:12:08.141  39                 0.356411         0.405338            0.750326        5.68162          0.276451                         0.354097           0.399603              0.762654          4.03297            0.259761\n",
       "    2017-07-13 09:36:41  10:12:49.269  184                0.354123         0.400313            0.759747        5.68638          0.272485                         0.35343            0.398184              0.766118          4.12136            0.251796\n",
       "    2017-07-13 09:39:38  10:15:45.872  800                0.353575         0.399189            0.76197         5.68638          0.259191                         0.353314           0.397914              0.766551          4.17661            0.258414"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable Importances: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>variable</b></td>\n",
       "<td><b>relative_importance</b></td>\n",
       "<td><b>scaled_importance</b></td>\n",
       "<td><b>percentage</b></td></tr>\n",
       "<tr><td>living_region</td>\n",
       "<td>617798.4375000</td>\n",
       "<td>1.0</td>\n",
       "<td>0.2153596</td></tr>\n",
       "<tr><td>tariff_id</td>\n",
       "<td>303094.8750000</td>\n",
       "<td>0.4906048</td>\n",
       "<td>0.1056564</td></tr>\n",
       "<tr><td>score_shk</td>\n",
       "<td>130313.2734375</td>\n",
       "<td>0.2109317</td>\n",
       "<td>0.0454262</td></tr>\n",
       "<tr><td>score_sq</td>\n",
       "<td>128976.0234375</td>\n",
       "<td>0.2087672</td>\n",
       "<td>0.0449600</td></tr>\n",
       "<tr><td>credit_sum</td>\n",
       "<td>126562.0781250</td>\n",
       "<td>0.2048598</td>\n",
       "<td>0.0441185</td></tr>\n",
       "<tr><td>---</td>\n",
       "<td>---</td>\n",
       "<td>---</td>\n",
       "<td>---</td></tr>\n",
       "<tr><td>monthly_income</td>\n",
       "<td>61428.6171875</td>\n",
       "<td>0.0994315</td>\n",
       "<td>0.0214135</td></tr>\n",
       "<tr><td>marital_status</td>\n",
       "<td>55896.8671875</td>\n",
       "<td>0.0904775</td>\n",
       "<td>0.0194852</td></tr>\n",
       "<tr><td>income_sq</td>\n",
       "<td>45024.8007812</td>\n",
       "<td>0.0728794</td>\n",
       "<td>0.0156953</td></tr>\n",
       "<tr><td>credit_count_sq</td>\n",
       "<td>31475.5703125</td>\n",
       "<td>0.0509480</td>\n",
       "<td>0.0109721</td></tr>\n",
       "<tr><td>gender</td>\n",
       "<td>30829.8085938</td>\n",
       "<td>0.0499027</td>\n",
       "<td>0.0107470</td></tr></table></div>"
      ],
      "text/plain": [
       "variable         relative_importance    scaled_importance     percentage\n",
       "---------------  ---------------------  --------------------  --------------------\n",
       "living_region    617798.4375            1.0                   0.21535958086607487\n",
       "tariff_id        303094.875             0.490604793735821     0.10565644274983352\n",
       "score_shk        130313.2734375         0.21093169799009082   0.04542616207051545\n",
       "score_sq         128976.0234375         0.20876715706730806   0.044960007444617485\n",
       "credit_sum       126562.078125          0.20485982230248034   0.04411852546736074\n",
       "---              ---                    ---                   ---\n",
       "monthly_income   61428.6171875          0.09943148680673056   0.021413523323588146\n",
       "marital_status   55896.8671875          0.09047751466270097   0.019485199635563423\n",
       "income_sq        45024.80078125         0.07287943453442289   0.015695284475089857\n",
       "credit_count_sq  31475.5703125          0.05094796037340253   0.01097213139199736\n",
       "gender           30829.80859375         0.049902697582898954  0.010747024035539607"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "See the whole table with table.as_data_frame()\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "optmodel = gridperf2.models[0]\n",
    "optmodel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mortgage</th>\n",
       "      <th>life_ins</th>\n",
       "      <th>cre_card</th>\n",
       "      <th>deb_card</th>\n",
       "      <th>mob_bank</th>\n",
       "      <th>curr_acc</th>\n",
       "      <th>internet</th>\n",
       "      <th>perloan</th>\n",
       "      <th>savings</th>\n",
       "      <th>atm_user</th>\n",
       "      <th>markpl</th>\n",
       "      <th>age</th>\n",
       "      <th>cus_leng</th>\n",
       "      <th>response</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>18</td>\n",
       "      <td>less than 3 years</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>18</td>\n",
       "      <td>from 3 to 7 years</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18</td>\n",
       "      <td>from 3 to 7 years</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>18</td>\n",
       "      <td>from 3 to 7 years</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>18</td>\n",
       "      <td>from 3 to 7 years</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  mortgage life_ins cre_card deb_card mob_bank curr_acc internet perloan  \\\n",
       "0       No       No       No       No       No       No       No      No   \n",
       "1      Yes      Yes       No      Yes      Yes       No       No      No   \n",
       "2      Yes      Yes       No      Yes       No       No       No      No   \n",
       "3      Yes      Yes      Yes      Yes       No      Yes       No      No   \n",
       "4      Yes      Yes       No      Yes       No       No       No     Yes   \n",
       "\n",
       "  savings atm_user markpl  age           cus_leng response  \n",
       "0      No       No     No   18  less than 3 years       No  \n",
       "1      No      Yes     No   18  from 3 to 7 years      Yes  \n",
       "2      No       No    Yes   18  from 3 to 7 years      Yes  \n",
       "3      No      Yes    Yes   18  from 3 to 7 years      Yes  \n",
       "4      No      Yes     No   18  from 3 to 7 years       No  "
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "example = pd.read_csv(\"C:/Trees/ResponsePy.csv\", encoding='cp1251', sep=';')\n",
    "example.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 30259 entries, 0 to 30258\n",
      "Data columns (total 14 columns):\n",
      "mortgage    30259 non-null object\n",
      "life_ins    30259 non-null object\n",
      "cre_card    30259 non-null object\n",
      "deb_card    30259 non-null object\n",
      "mob_bank    30259 non-null object\n",
      "curr_acc    30259 non-null object\n",
      "internet    30259 non-null object\n",
      "perloan     30259 non-null object\n",
      "savings     30259 non-null object\n",
      "atm_user    30259 non-null object\n",
      "markpl      30259 non-null object\n",
      "age         30259 non-null int64\n",
      "cus_leng    30259 non-null object\n",
      "response    30259 non-null object\n",
      "dtypes: int64(1), object(13)\n",
      "memory usage: 3.2+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(example.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parse progress: |█████████████████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "fr = h2o.H2OFrame(example)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rows:30259\n",
      "Cols:14\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>       </th><th>mortgage  </th><th>life_ins  </th><th>cre_card  </th><th>deb_card  </th><th>mob_bank  </th><th>curr_acc  </th><th>internet  </th><th>perloan  </th><th>savings  </th><th>atm_user  </th><th>markpl  </th><th>age              </th><th>cus_leng         </th><th>response  </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td>type   </td><td>enum      </td><td>enum      </td><td>enum      </td><td>enum      </td><td>enum      </td><td>enum      </td><td>enum      </td><td>enum     </td><td>enum     </td><td>enum      </td><td>enum    </td><td>int              </td><td>enum             </td><td>enum      </td></tr>\n",
       "<tr><td>mins   </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>         </td><td>         </td><td>          </td><td>        </td><td>18.0             </td><td>                 </td><td>          </td></tr>\n",
       "<tr><td>mean   </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>         </td><td>         </td><td>          </td><td>        </td><td>43.43362305429792</td><td>                 </td><td>          </td></tr>\n",
       "<tr><td>maxs   </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>         </td><td>         </td><td>          </td><td>        </td><td>63.0             </td><td>                 </td><td>          </td></tr>\n",
       "<tr><td>sigma  </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>         </td><td>         </td><td>          </td><td>        </td><td>10.93940042180055</td><td>                 </td><td>          </td></tr>\n",
       "<tr><td>zeros  </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>          </td><td>         </td><td>         </td><td>          </td><td>        </td><td>0                </td><td>                 </td><td>          </td></tr>\n",
       "<tr><td>missing</td><td>0         </td><td>0         </td><td>0         </td><td>0         </td><td>0         </td><td>0         </td><td>0         </td><td>0        </td><td>0        </td><td>0         </td><td>0       </td><td>0                </td><td>0                </td><td>0         </td></tr>\n",
       "<tr><td>0      </td><td>No        </td><td>No        </td><td>No        </td><td>No        </td><td>No        </td><td>No        </td><td>No        </td><td>No       </td><td>No       </td><td>No        </td><td>No      </td><td>18.0             </td><td>less than 3 years</td><td>No        </td></tr>\n",
       "<tr><td>1      </td><td>Yes       </td><td>Yes       </td><td>No        </td><td>Yes       </td><td>Yes       </td><td>No        </td><td>No        </td><td>No       </td><td>No       </td><td>Yes       </td><td>No      </td><td>18.0             </td><td>from 3 to 7 years</td><td>Yes       </td></tr>\n",
       "<tr><td>2      </td><td>Yes       </td><td>Yes       </td><td>No        </td><td>Yes       </td><td>No        </td><td>No        </td><td>No        </td><td>No       </td><td>No       </td><td>No        </td><td>Yes     </td><td>18.0             </td><td>from 3 to 7 years</td><td>Yes       </td></tr>\n",
       "<tr><td>3      </td><td>Yes       </td><td>Yes       </td><td>Yes       </td><td>Yes       </td><td>No        </td><td>Yes       </td><td>No        </td><td>No       </td><td>No       </td><td>Yes       </td><td>Yes     </td><td>18.0             </td><td>from 3 to 7 years</td><td>Yes       </td></tr>\n",
       "<tr><td>4      </td><td>Yes       </td><td>Yes       </td><td>No        </td><td>Yes       </td><td>No        </td><td>No        </td><td>No        </td><td>Yes      </td><td>No       </td><td>Yes       </td><td>No      </td><td>18.0             </td><td>from 3 to 7 years</td><td>No        </td></tr>\n",
       "<tr><td>5      </td><td>No        </td><td>No        </td><td>No        </td><td>Yes       </td><td>Yes       </td><td>Yes       </td><td>No        </td><td>No       </td><td>No       </td><td>No        </td><td>No      </td><td>18.0             </td><td>from 3 to 7 years</td><td>Yes       </td></tr>\n",
       "<tr><td>6      </td><td>No        </td><td>No        </td><td>No        </td><td>Yes       </td><td>No        </td><td>No        </td><td>No        </td><td>No       </td><td>No       </td><td>Yes       </td><td>No      </td><td>18.0             </td><td>less than 3 years</td><td>Yes       </td></tr>\n",
       "<tr><td>7      </td><td>Yes       </td><td>Yes       </td><td>No        </td><td>Yes       </td><td>No        </td><td>No        </td><td>No        </td><td>No       </td><td>No       </td><td>Yes       </td><td>No      </td><td>18.0             </td><td>less than 3 years</td><td>Yes       </td></tr>\n",
       "<tr><td>8      </td><td>Yes       </td><td>Yes       </td><td>No        </td><td>Yes       </td><td>No        </td><td>No        </td><td>No        </td><td>No       </td><td>No       </td><td>Yes       </td><td>Yes     </td><td>18.0             </td><td>more than 7 years</td><td>No        </td></tr>\n",
       "<tr><td>9      </td><td>Yes       </td><td>Yes       </td><td>Yes       </td><td>Yes       </td><td>No        </td><td>Yes       </td><td>No        </td><td>No       </td><td>No       </td><td>No        </td><td>No      </td><td>18.0             </td><td>from 3 to 7 years</td><td>Yes       </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fr.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "dependent = 'response'\n",
    "predictors = list(example.columns)\n",
    "predictors.remove(dependent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "splits = fr.split_frame(ratios=[0.7, 0.15], seed=10000)  \n",
    "tr = splits[0]\n",
    "valid = splits[1]\n",
    "test = splits[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "21260\n",
      "4471\n",
      "4528\n"
     ]
    }
   ],
   "source": [
    "print(tr.nrow)\n",
    "print(valid.nrow)\n",
    "print(test.nrow)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "drf Grid Build progress: |████████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "hyper_parameters = {'mtries': [3, 5, 7, 9], 'max_depth': [10, 12, 14, 16]}\n",
    "gridsearch3 = H2OGridSearch(H2ORandomForestEstimator, grid_id=\"mygrid3\",   \n",
    "                           hyper_params=hyper_parameters)\n",
    "gridsearch3.train(x=predictors, y=dependent, \n",
    "                  ntrees=300, training_frame=tr, validation_frame=valid, \n",
    "                  seed=1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     max_depth mtries         model_ids                 auc\n",
      "0           10      3   mygrid3_model_0   0.916135430596348\n",
      "1           12      3   mygrid3_model_1  0.9157340522321074\n",
      "2           10      5   mygrid3_model_4  0.9156111148426543\n",
      "3           14      3   mygrid3_model_2  0.9151885684510906\n",
      "4           16      3   mygrid3_model_3  0.9147241948516914\n",
      "5           10      7   mygrid3_model_8  0.9142755955034225\n",
      "6           12      5   mygrid3_model_5  0.9128929569495244\n",
      "7           10      9  mygrid3_model_12  0.9128157140036678\n",
      "8           12      7   mygrid3_model_9  0.9097974382616164\n",
      "9           14      5   mygrid3_model_6  0.9084124590123894\n",
      "10          12      9  mygrid3_model_13   0.907894656497872\n",
      "11          14      7  mygrid3_model_10  0.9033587960277383\n",
      "12          16      5   mygrid3_model_7  0.9027679231112115\n",
      "13          14      9  mygrid3_model_14  0.9011175293655493\n",
      "14          16      7  mygrid3_model_11  0.8958920796976229\n",
      "15          16      9  mygrid3_model_15  0.8930666568968079\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gridperf3 = gridsearch3.get_grid(sort_by='auc', decreasing=True)\n",
    "gridperf3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.91079871144299\n"
     ]
    }
   ],
   "source": [
    "finalmodel = gridperf3.models[0]\n",
    "finalmodel_perf = finalmodel.model_performance(test)\n",
    "print(finalmodel_perf.auc())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Улучшение качества модели с помощью стекинга"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from h2o.estimators import H2OGradientBoostingEstimator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gbm = H2OGradientBoostingEstimator(distribution=\"bernoulli\", learn_rate=0.09, ntrees=250, max_depth=4, min_rows=6, \n",
    "                                   sample_rate=0.85, col_sample_rate = 0.6, histogram_type=\"RoundRobin\", \n",
    "                                   nfolds=5, fold_assignment=\"Modulo\", keep_cross_validation_predictions=True, \n",
    "                                   seed=1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gbm Model Build progress: |███████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "gbm.train(X, y, training_frame=training, validation_frame=validation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "drf Model Build progress: |███████████████████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "rf = H2ORandomForestEstimator(ntrees=800, max_depth=14, \n",
    "                              nfolds=5, fold_assignment=\"Modulo\",\n",
    "                              keep_cross_validation_predictions=True, seed=1000000)\n",
    "rf.train(X, y, training_frame=training, validation_frame=validation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from h2o.estimators import H2OStackedEnsembleEstimator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stackedensemble Model Build progress: |███████████████████████████████████| 100%\n"
     ]
    }
   ],
   "source": [
    "ensemble = H2OStackedEnsembleEstimator(model_id=\"my_ensemble\", base_models=[gbm.model_id, rf.model_id])\n",
    "ensemble.train(X, y, training_frame=training)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ModelMetricsBinomialGLM: stackedensemble\n",
      "** Reported on test data. **\n",
      "\n",
      "MSE: 0.12534839717166807\n",
      "RMSE: 0.35404575575999786\n",
      "LogLoss: 0.4013247770573431\n",
      "Null degrees of freedom: 51223\n",
      "Residual degrees of freedom: 51221\n",
      "Null deviance: 47733.00986180187\n",
      "Residual deviance: 41114.920759970686\n",
      "AIC: 41120.920759970686\n",
      "AUC: 0.7707808685074398\n",
      "Gini: 0.5415617370148795\n",
      "Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.1783515934603045: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>0</b></td>\n",
       "<td><b>1</b></td>\n",
       "<td><b>Error</b></td>\n",
       "<td><b>Rate</b></td></tr>\n",
       "<tr><td>0</td>\n",
       "<td>31660.0</td>\n",
       "<td>10527.0</td>\n",
       "<td>0.2495</td>\n",
       "<td> (10527.0/42187.0)</td></tr>\n",
       "<tr><td>1</td>\n",
       "<td>3213.0</td>\n",
       "<td>5824.0</td>\n",
       "<td>0.3555</td>\n",
       "<td> (3213.0/9037.0)</td></tr>\n",
       "<tr><td>Total</td>\n",
       "<td>34873.0</td>\n",
       "<td>16351.0</td>\n",
       "<td>0.2682</td>\n",
       "<td> (13740.0/51224.0)</td></tr></table></div>"
      ],
      "text/plain": [
       "       0      1      Error    Rate\n",
       "-----  -----  -----  -------  -----------------\n",
       "0      31660  10527  0.2495   (10527.0/42187.0)\n",
       "1      3213   5824   0.3555   (3213.0/9037.0)\n",
       "Total  34873  16351  0.2682   (13740.0/51224.0)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Metrics: Maximum metrics at their respective thresholds\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b>metric</b></td>\n",
       "<td><b>threshold</b></td>\n",
       "<td><b>value</b></td>\n",
       "<td><b>idx</b></td></tr>\n",
       "<tr><td>max f1</td>\n",
       "<td>0.1783516</td>\n",
       "<td>0.4587994</td>\n",
       "<td>273.0</td></tr>\n",
       "<tr><td>max f2</td>\n",
       "<td>0.1088766</td>\n",
       "<td>0.6045959</td>\n",
       "<td>333.0</td></tr>\n",
       "<tr><td>max f0point5</td>\n",
       "<td>0.2914525</td>\n",
       "<td>0.4290382</td>\n",
       "<td>201.0</td></tr>\n",
       "<tr><td>max accuracy</td>\n",
       "<td>0.5936857</td>\n",
       "<td>0.8307239</td>\n",
       "<td>78.0</td></tr>\n",
       "<tr><td>max precision</td>\n",
       "<td>0.9543844</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max recall</td>\n",
       "<td>0.0581408</td>\n",
       "<td>1.0</td>\n",
       "<td>398.0</td></tr>\n",
       "<tr><td>max specificity</td>\n",
       "<td>0.9543844</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0</td></tr>\n",
       "<tr><td>max absolute_mcc</td>\n",
       "<td>0.1783516</td>\n",
       "<td>0.3229272</td>\n",
       "<td>273.0</td></tr>\n",
       "<tr><td>max min_per_class_accuracy</td>\n",
       "<td>0.1563775</td>\n",
       "<td>0.7008083</td>\n",
       "<td>290.0</td></tr>\n",
       "<tr><td>max mean_per_class_accuracy</td>\n",
       "<td>0.1541980</td>\n",
       "<td>0.7026276</td>\n",
       "<td>292.0</td></tr></table></div>"
      ],
      "text/plain": [
       "metric                       threshold    value     idx\n",
       "---------------------------  -----------  --------  -----\n",
       "max f1                       0.178352     0.458799  273\n",
       "max f2                       0.108877     0.604596  333\n",
       "max f0point5                 0.291452     0.429038  201\n",
       "max accuracy                 0.593686     0.830724  78\n",
       "max precision                0.954384     1         0\n",
       "max recall                   0.0581408    1         398\n",
       "max specificity              0.954384     1         0\n",
       "max absolute_mcc             0.178352     0.322927  273\n",
       "max min_per_class_accuracy   0.156377     0.700808  290\n",
       "max mean_per_class_accuracy  0.154198     0.702628  292"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gains/Lift Table: Avg response rate: 17,64 %\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td><b></b></td>\n",
       "<td><b>group</b></td>\n",
       "<td><b>cumulative_data_fraction</b></td>\n",
       "<td><b>lower_threshold</b></td>\n",
       "<td><b>lift</b></td>\n",
       "<td><b>cumulative_lift</b></td>\n",
       "<td><b>response_rate</b></td>\n",
       "<td><b>cumulative_response_rate</b></td>\n",
       "<td><b>capture_rate</b></td>\n",
       "<td><b>cumulative_capture_rate</b></td>\n",
       "<td><b>gain</b></td>\n",
       "<td><b>cumulative_gain</b></td></tr>\n",
       "<tr><td></td>\n",
       "<td>1</td>\n",
       "<td>0.0100148</td>\n",
       "<td>0.7705341</td>\n",
       "<td>4.2539519</td>\n",
       "<td>4.2539519</td>\n",
       "<td>0.7504873</td>\n",
       "<td>0.7504873</td>\n",
       "<td>0.0426026</td>\n",
       "<td>0.0426026</td>\n",
       "<td>325.3951860</td>\n",
       "<td>325.3951860</td></tr>\n",
       "<tr><td></td>\n",
       "<td>2</td>\n",
       "<td>0.0200102</td>\n",
       "<td>0.6528723</td>\n",
       "<td>3.2548170</td>\n",
       "<td>3.7548718</td>\n",
       "<td>0.5742188</td>\n",
       "<td>0.6624390</td>\n",
       "<td>0.0325329</td>\n",
       "<td>0.0751356</td>\n",
       "<td>225.4817002</td>\n",
       "<td>275.4871814</td></tr>\n",
       "<tr><td></td>\n",
       "<td>3</td>\n",
       "<td>0.0300055</td>\n",
       "<td>0.5706241</td>\n",
       "<td>3.0112593</td>\n",
       "<td>3.5071622</td>\n",
       "<td>0.53125</td>\n",
       "<td>0.6187378</td>\n",
       "<td>0.0300985</td>\n",
       "<td>0.1052340</td>\n",
       "<td>201.1259267</td>\n",
       "<td>250.7162235</td></tr>\n",
       "<tr><td></td>\n",
       "<td>4</td>\n",
       "<td>0.0400008</td>\n",
       "<td>0.5110191</td>\n",
       "<td>2.6016394</td>\n",
       "<td>3.2808920</td>\n",
       "<td>0.4589844</td>\n",
       "<td>0.5788189</td>\n",
       "<td>0.0260042</td>\n",
       "<td>0.1312382</td>\n",
       "<td>160.1639441</td>\n",
       "<td>228.0892020</td></tr>\n",
       "<tr><td></td>\n",
       "<td>5</td>\n",
       "<td>0.0500156</td>\n",
       "<td>0.4718957</td>\n",
       "<td>2.6297157</td>\n",
       "<td>3.1505043</td>\n",
       "<td>0.4639376</td>\n",
       "<td>0.5558158</td>\n",
       "<td>0.0263362</td>\n",
       "<td>0.1575744</td>\n",
       "<td>162.9715696</td>\n",
       "<td>215.0504254</td></tr>\n",
       "<tr><td></td>\n",
       "<td>6</td>\n",
       "<td>0.1000117</td>\n",
       "<td>0.3702920</td>\n",
       "<td>2.3859338</td>\n",
       "<td>2.7682936</td>\n",
       "<td>0.4209293</td>\n",
       "<td>0.4883857</td>\n",
       "<td>0.1192874</td>\n",
       "<td>0.2768618</td>\n",
       "<td>138.5933796</td>\n",
       "<td>176.8293647</td></tr>\n",
       "<tr><td></td>\n",
       "<td>7</td>\n",
       "<td>0.1500078</td>\n",
       "<td>0.3055798</td>\n",
       "<td>1.9809005</td>\n",
       "<td>2.5058634</td>\n",
       "<td>0.3494729</td>\n",
       "<td>0.4420875</td>\n",
       "<td>0.0990373</td>\n",
       "<td>0.3758991</td>\n",
       "<td>98.0900508</td>\n",
       "<td>150.5863424</td></tr>\n",
       "<tr><td></td>\n",
       "<td>8</td>\n",
       "<td>0.2000039</td>\n",
       "<td>0.2561726</td>\n",
       "<td>1.8038368</td>\n",
       "<td>2.3303739</td>\n",
       "<td>0.3182351</td>\n",
       "<td>0.4111274</td>\n",
       "<td>0.0901848</td>\n",
       "<td>0.4660839</td>\n",
       "<td>80.3836776</td>\n",
       "<td>133.0373893</td></tr>\n",
       "<tr><td></td>\n",
       "<td>9</td>\n",
       "<td>0.2999961</td>\n",
       "<td>0.1872011</td>\n",
       "<td>1.5105750</td>\n",
       "<td>2.0571254</td>\n",
       "<td>0.2664975</td>\n",
       "<td>0.3629205</td>\n",
       "<td>0.1510457</td>\n",
       "<td>0.6171296</td>\n",
       "<td>51.0574968</td>\n",
       "<td>105.7125368</td></tr>\n",
       "<tr><td></td>\n",
       "<td>10</td>\n",
       "<td>0.4000078</td>\n",
       "<td>0.1443212</td>\n",
       "<td>1.1506896</td>\n",
       "<td>1.8304943</td>\n",
       "<td>0.2030061</td>\n",
       "<td>0.3229380</td>\n",
       "<td>0.1150824</td>\n",
       "<td>0.7322120</td>\n",
       "<td>15.0689605</td>\n",
       "<td>83.0494308</td></tr>\n",
       "<tr><td></td>\n",
       "<td>11</td>\n",
       "<td>0.5</td>\n",
       "<td>0.1144761</td>\n",
       "<td>0.9306912</td>\n",
       "<td>1.6505477</td>\n",
       "<td>0.1641937</td>\n",
       "<td>0.2911916</td>\n",
       "<td>0.0930619</td>\n",
       "<td>0.8252739</td>\n",
       "<td>-6.9308756</td>\n",
       "<td>65.0547748</td></tr>\n",
       "<tr><td></td>\n",
       "<td>12</td>\n",
       "<td>0.5999922</td>\n",
       "<td>0.0950188</td>\n",
       "<td>0.6529225</td>\n",
       "<td>1.4842877</td>\n",
       "<td>0.1151894</td>\n",
       "<td>0.2618598</td>\n",
       "<td>0.0652872</td>\n",
       "<td>0.8905610</td>\n",
       "<td>-34.7077486</td>\n",
       "<td>48.4287696</td></tr>\n",
       "<tr><td></td>\n",
       "<td>13</td>\n",
       "<td>0.7000039</td>\n",
       "<td>0.0842095</td>\n",
       "<td>0.4503180</td>\n",
       "<td>1.3365613</td>\n",
       "<td>0.0794456</td>\n",
       "<td>0.2357978</td>\n",
       "<td>0.0450371</td>\n",
       "<td>0.9355981</td>\n",
       "<td>-54.9682049</td>\n",
       "<td>33.6561255</td></tr>\n",
       "<tr><td></td>\n",
       "<td>14</td>\n",
       "<td>0.7999961</td>\n",
       "<td>0.0774742</td>\n",
       "<td>0.3319945</td>\n",
       "<td>1.2109996</td>\n",
       "<td>0.0585709</td>\n",
       "<td>0.2136460</td>\n",
       "<td>0.0331969</td>\n",
       "<td>0.9687950</td>\n",
       "<td>-66.8005501</td>\n",
       "<td>21.0999603</td></tr>\n",
       "<tr><td></td>\n",
       "<td>15</td>\n",
       "<td>0.8999883</td>\n",
       "<td>0.0701738</td>\n",
       "<td>0.2169031</td>\n",
       "<td>1.1005516</td>\n",
       "<td>0.0382663</td>\n",
       "<td>0.1941606</td>\n",
       "<td>0.0216886</td>\n",
       "<td>0.9904836</td>\n",
       "<td>-78.3096928</td>\n",
       "<td>10.0551621</td></tr>\n",
       "<tr><td></td>\n",
       "<td>16</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0553408</td>\n",
       "<td>0.0951532</td>\n",
       "<td>1.0</td>\n",
       "<td>0.0167870</td>\n",
       "<td>0.1764212</td>\n",
       "<td>0.0095164</td>\n",
       "<td>1.0</td>\n",
       "<td>-90.4846821</td>\n",
       "<td>0.0</td></tr></table></div>"
      ],
      "text/plain": [
       "    group    cumulative_data_fraction    lower_threshold    lift       cumulative_lift    response_rate    cumulative_response_rate    capture_rate    cumulative_capture_rate    gain      cumulative_gain\n",
       "--  -------  --------------------------  -----------------  ---------  -----------------  ---------------  --------------------------  --------------  -------------------------  --------  -----------------\n",
       "    1        0.0100148                   0.770534           4.25395    4.25395            0.750487         0.750487                    0.0426026       0.0426026                  325.395   325.395\n",
       "    2        0.0200102                   0.652872           3.25482    3.75487            0.574219         0.662439                    0.0325329       0.0751356                  225.482   275.487\n",
       "    3        0.0300055                   0.570624           3.01126    3.50716            0.53125          0.618738                    0.0300985       0.105234                   201.126   250.716\n",
       "    4        0.0400008                   0.511019           2.60164    3.28089            0.458984         0.578819                    0.0260042       0.131238                   160.164   228.089\n",
       "    5        0.0500156                   0.471896           2.62972    3.1505             0.463938         0.555816                    0.0263362       0.157574                   162.972   215.05\n",
       "    6        0.100012                    0.370292           2.38593    2.76829            0.420929         0.488386                    0.119287        0.276862                   138.593   176.829\n",
       "    7        0.150008                    0.30558            1.9809     2.50586            0.349473         0.442087                    0.0990373       0.375899                   98.0901   150.586\n",
       "    8        0.200004                    0.256173           1.80384    2.33037            0.318235         0.411127                    0.0901848       0.466084                   80.3837   133.037\n",
       "    9        0.299996                    0.187201           1.51057    2.05713            0.266497         0.362921                    0.151046        0.61713                    51.0575   105.713\n",
       "    10       0.400008                    0.144321           1.15069    1.83049            0.203006         0.322938                    0.115082        0.732212                   15.069    83.0494\n",
       "    11       0.5                         0.114476           0.930691   1.65055            0.164194         0.291192                    0.0930619       0.825274                   -6.93088  65.0548\n",
       "    12       0.599992                    0.0950188          0.652923   1.48429            0.115189         0.26186                     0.0652872       0.890561                   -34.7077  48.4288\n",
       "    13       0.700004                    0.0842095          0.450318   1.33656            0.0794456        0.235798                    0.0450371       0.935598                   -54.9682  33.6561\n",
       "    14       0.799996                    0.0774742          0.331994   1.211              0.0585709        0.213646                    0.0331969       0.968795                   -66.8006  21.1\n",
       "    15       0.899988                    0.0701738          0.216903   1.10055            0.0382663        0.194161                    0.0216886       0.990484                   -78.3097  10.0552\n",
       "    16       1                           0.0553408          0.0951532  1                  0.016787         0.176421                    0.00951643      1                          -90.4847  0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perf_stack_validation = ensemble.model_performance(validation)\n",
    "perf_stack_validation"
   ]
  }
 ],
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