Haberman_Problem.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# AGENDA OF DATA"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "1.Age of patient at time of operation (numerical)\n",
    "2.Patient's year of operation (year - 1900, numerical)\n",
    "3.Number of positive axillary nodes detected (numerical)\n",
    "4.Survival statuS::: 1 = the patient survived 5 years or longer, 2 = the patient died within 5 years"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### CHECKING SYSTEM CONFIGURATION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'commit_hash': 'd774f565b',\n",
      " 'commit_source': 'installation',\n",
      " 'default_encoding': 'cp1252',\n",
      " 'ipython_path': 'C:\\\\Anaconda\\\\lib\\\\site-packages\\\\IPython',\n",
      " 'ipython_version': '7.4.0',\n",
      " 'os_name': 'nt',\n",
      " 'platform': 'Windows-10-10.0.18362-SP0',\n",
      " 'sys_executable': 'C:\\\\Anaconda\\\\python.exe',\n",
      " 'sys_platform': 'win32',\n",
      " 'sys_version': '3.7.3 (default, Mar 27 2019, 17:13:21) [MSC v.1915 64 bit '\n",
      "                '(AMD64)]'}\n"
     ]
    }
   ],
   "source": [
    "import IPython\n",
    "print(IPython.sys_info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing the dataset and giving the heads to the columns and initiating eda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>operation_year</th>\n",
       "      <th>nodes</th>\n",
       "      <th>survived_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30</td>\n",
       "      <td>64</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <th>1</th>\n",
       "      <td>30</td>\n",
       "      <td>62</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>31</td>\n",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
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       "      <th>4</th>\n",
       "      <td>31</td>\n",
       "      <td>65</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>33</td>\n",
       "      <td>58</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>33</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>34</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>34</td>\n",
       "      <td>66</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>34</td>\n",
       "      <td>58</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  operation_year  nodes  survived_status\n",
       "0   30              64      1                1\n",
       "1   30              62      3                1\n",
       "2   30              65      0                1\n",
       "3   31              59      2                1\n",
       "4   31              65      4                1\n",
       "5   33              58     10                1\n",
       "6   33              60      0                1\n",
       "7   34              59      0                2\n",
       "8   34              66      9                2\n",
       "9   34              58     30                1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "haberman_dataset = pd.read_csv(r\"C:\\Users\\HP\\Desktop\\Haberman_dataset.csv\", header=None, names=['age', 'operation_year', 'nodes', 'survived_status'])\n",
    "haberman_dataset.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(306, 4)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "haberman_dataset.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'operation_year', 'nodes', 'survived_status'], dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "haberman_dataset.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>operation_year</th>\n",
       "      <th>nodes</th>\n",
       "      <th>survived_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>306.000000</td>\n",
       "      <td>306.000000</td>\n",
       "      <td>306.000000</td>\n",
       "      <td>306.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>52.457516</td>\n",
       "      <td>62.852941</td>\n",
       "      <td>4.026144</td>\n",
       "      <td>1.264706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>10.803452</td>\n",
       "      <td>3.249405</td>\n",
       "      <td>7.189654</td>\n",
       "      <td>0.441899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>44.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>52.000000</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>60.750000</td>\n",
       "      <td>65.750000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>83.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age  operation_year       nodes  survived_status\n",
       "count  306.000000      306.000000  306.000000       306.000000\n",
       "mean    52.457516       62.852941    4.026144         1.264706\n",
       "std     10.803452        3.249405    7.189654         0.441899\n",
       "min     30.000000       58.000000    0.000000         1.000000\n",
       "25%     44.000000       60.000000    0.000000         1.000000\n",
       "50%     52.000000       63.000000    1.000000         1.000000\n",
       "75%     60.750000       65.750000    4.000000         2.000000\n",
       "max     83.000000       69.000000   52.000000         2.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "haberman_dataset.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 306 entries, 0 to 305\n",
      "Data columns (total 4 columns):\n",
      " #   Column           Non-Null Count  Dtype\n",
      "---  ------           --------------  -----\n",
      " 0   age              306 non-null    int64\n",
      " 1   operation_year   306 non-null    int64\n",
      " 2   nodes            306 non-null    int64\n",
      " 3   survived_status  306 non-null    int64\n",
      "dtypes: int64(4)\n",
      "memory usage: 9.7 KB\n"
     ]
    }
   ],
   "source": [
    "haberman_dataset.info()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "from the data found that no missing value found in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variable 0\n",
      "\tname: age\n",
      "\ttype: <class 'numpy.int64'>\n",
      "\tUnique Values: [30 31 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54\n",
      " 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78\n",
      " 83]\n",
      "Variable 1\n",
      "\tname: operation_year\n",
      "\ttype: <class 'numpy.int64'>\n",
      "\tUnique Values: [64 62 65 59 58 60 66 61 67 63 69 68]\n",
      "Variable 2\n",
      "\tname: nodes\n",
      "\ttype: <class 'numpy.int64'>\n",
      "\tUnique Values: [ 1  3  0  2  4 10  9 30  7 13  6 15 21 11  5 23  8 20 52 14 19 16 12 24\n",
      " 46 18 22 35 17 25 28]\n",
      "Variable 3\n",
      "\tname: survived_status\n",
      "\ttype: <class 'numpy.int64'>\n",
      "\tUnique Values: [1 2]\n"
     ]
    }
   ],
   "source": [
    "for n, c in enumerate(haberman_dataset.columns):\n",
    "    print('Variable {}\\n\\tname: {}\\n\\ttype: {}'.format(n, c, type(haberman_dataset.iloc[0, n])))\n",
    "    print('\\tUnique Values: {}'.format(haberman_dataset[c].unique()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating a copy of original dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "haberman_dataset_cleaned = haberman_dataset.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "      <th>3</th>\n",
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       "      <th>4</th>\n",
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       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "   age  operation_year  nodes  survived_status\n",
       "0   30              64      1                1\n",
       "1   30              62      3                1\n",
       "2   30              65      0                1\n",
       "3   31              59      2                1\n",
       "4   31              65      4                1"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "haberman_dataset_cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(306, 4)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "haberman_dataset_cleaned.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### No Missing value were found in our dataset, but we need to label our class in readable format, as survived features say 1 means survived which can be decoded as 'survived', and 2- not survived which can b labeled as 'dead'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "      <th>7</th>\n",
       "      <td>34</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>Didntsurvive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>34</td>\n",
       "      <td>66</td>\n",
       "      <td>9</td>\n",
       "      <td>Didntsurvive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>34</td>\n",
       "      <td>58</td>\n",
       "      <td>30</td>\n",
       "      <td>Survived</td>\n",
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       "      <th>10</th>\n",
       "      <td>34</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>34</td>\n",
       "      <td>61</td>\n",
       "      <td>10</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>34</td>\n",
       "      <td>67</td>\n",
       "      <td>7</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>34</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>35</td>\n",
       "      <td>64</td>\n",
       "      <td>13</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>35</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>36</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>36</td>\n",
       "      <td>69</td>\n",
       "      <td>0</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>37</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>37</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>Survived</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    age  operation_year  nodes survived_status\n",
       "0    30              64      1        Survived\n",
       "1    30              62      3        Survived\n",
       "2    30              65      0        Survived\n",
       "3    31              59      2        Survived\n",
       "4    31              65      4        Survived\n",
       "5    33              58     10        Survived\n",
       "6    33              60      0        Survived\n",
       "7    34              59      0    Didntsurvive\n",
       "8    34              66      9    Didntsurvive\n",
       "9    34              58     30        Survived\n",
       "10   34              60      1        Survived\n",
       "11   34              61     10        Survived\n",
       "12   34              67      7        Survived\n",
       "13   34              60      0        Survived\n",
       "14   35              64     13        Survived\n",
       "15   35              63      0        Survived\n",
       "16   36              60      1        Survived\n",
       "17   36              69      0        Survived\n",
       "18   37              60      0        Survived\n",
       "19   37              63      0        Survived"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "haberman_dataset_cleaned['survived_status'] = haberman_dataset_cleaned['survived_status'].map({1:'Survived', 2:'Didntsurvive'})\n",
    "haberman_dataset_cleaned.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Survived        225\n",
       "Didntsurvive     81\n",
       "Name: survived_status, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "haberman_dataset_cleaned['survived_status'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(haberman_dataset_cleaned['age'],haberman_dataset_cleaned['operation_year'], c = 'g')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Operation year')\n",
    "plt.title('Operation year vs Age')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "This scatter plot doesn't clear much about the dataset, it seems that dataset is highly mixed up, but still we can say that the majority of operations are performed on people age range between 40 and 68, where most of the points plotted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(haberman_dataset_cleaned['age'],haberman_dataset_cleaned['nodes'], color = 'g')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Axil Nodes')\n",
    "plt.title('Axil_nodes vs Age')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "We can see that there is quite good concentration of data point When axil_node is 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(haberman_dataset_cleaned['nodes'], haberman_dataset_cleaned['operation_year'], c = 'g')\n",
    "plt.xlabel('Axil Nodes')\n",
    "plt.ylabel('Operation year')\n",
    "plt.title('Operation year vs Axil Nodes')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Here we can conclude that large number of operation were done in span of 7 years between 1960 and 1966"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pairplot Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 739.375x648 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# (PAIR PLOT)\n",
    "plt.close()\n",
    "sns.set_style(\"whitegrid\")\n",
    "sns.pairplot(haberman_dataset_cleaned,hue=\"survived_status\",height=3)\n",
    "plt.title(\"PAIR PLOT\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scatter Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 523.375x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style('whitegrid');\n",
    "sns.FacetGrid(haberman_dataset_cleaned, hue = 'survived_status', size = 6).map(plt.scatter, 'age', 'nodes').add_legend();\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 595.375x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style('whitegrid');\n",
    "sns.FacetGrid(haberman_dataset_cleaned, hue='survived_status', size = 7).map(plt.scatter, 'operation_year', 'nodes').add_legend();\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Shaping the histogram for PDF and CDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "haberman_survived=haberman_dataset_cleaned.loc[haberman_dataset_cleaned['survived_status']=='Survived']\n",
    "haberman_Didntsurvive=haberman_dataset_cleaned.loc[haberman_dataset_cleaned['survived_status']=='Didntsurvive']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(haberman_survived['nodes'],np.zeros_like(haberman_survived['nodes']),'o')\n",
    "plt.plot(haberman_Didntsurvive['nodes'],np.zeros_like(haberman_Didntsurvive['nodes']),'o')\n",
    "plt.title(\"Scatter Plot those who had Survived and Didn't Survived\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "from the graph we can evaluate the points are overlapping which is not providing the correct about the data so lets proceed further"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Univariate Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 451.375x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.FacetGrid(haberman_dataset_cleaned, hue=\"survived_status\", height=5).map(sns.distplot, \"nodes\").add_legend();\n",
    "plt.title(\"PDF of Nodes\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 451.375x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.FacetGrid(haberman_dataset_cleaned, hue=\"survived_status\", height=5).map(sns.distplot, \"operation_year\").add_legend();\n",
    "plt.title(\"PDF OF YEAR\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 451.375x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.FacetGrid(haberman_dataset_cleaned, hue=\"survived_status\", height=5).map(sns.distplot, \"age\").add_legend();\n",
    "plt.title(\"PDF OF age\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "observation:\n",
    "here with the observation the people with 0 nodes almost survived\n",
    "People with more nodes have less chance of survival or didn't survive\n",
    "Patients who are at the age of 30 have more chances of surviving\n",
    "if no of nodes==0 have long survival"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PDF & CDF OF AGE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.01633987 0.03594771 0.02614379 0.0620915  0.09803922 0.05228758\n",
      " 0.08169935 0.09150327 0.08169935 0.09803922 0.08496732 0.04901961\n",
      " 0.06535948 0.06862745 0.01960784 0.03921569 0.01633987 0.00653595\n",
      " 0.00326797 0.00326797]\n",
      "[30.   32.65 35.3  37.95 40.6  43.25 45.9  48.55 51.2  53.85 56.5  59.15\n",
      " 61.8  64.45 67.1  69.75 72.4  75.05 77.7  80.35 83.  ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "counts,bins=np.histogram(haberman_dataset_cleaned['age'], bins = 20, density = True)\n",
    "pdf=counts/(sum(counts))\n",
    "print(pdf)\n",
    "print(bins)\n",
    "\n",
    "#compute CDF\n",
    "cdf=np.cumsum(pdf)\n",
    "plt.plot(bins[1:],pdf,label='pdf')\n",
    "plt.plot(bins[1:],cdf,label='cdf')\n",
    "plt.xlabel('age')\n",
    "plt.ylabel('probability')\n",
    "plt.title(\"CDF AND PDF FOR THE AGE OF SURVIVED\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PDF & CDF OF NODES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.64379085 0.12745098 0.04575163 0.05228758 0.01960784 0.03921569\n",
      " 0.00980392 0.01633987 0.02287582 0.00653595 0.00326797 0.00326797\n",
      " 0.         0.00326797 0.         0.         0.         0.00326797\n",
      " 0.         0.00326797]\n",
      "[ 0.   2.6  5.2  7.8 10.4 13.  15.6 18.2 20.8 23.4 26.  28.6 31.2 33.8\n",
      " 36.4 39.  41.6 44.2 46.8 49.4 52. ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "counts, bin_edges = np.histogram(haberman_dataset_cleaned['nodes'], bins=20, density = True)\n",
    "pdf = counts/(sum(counts))\n",
    "print(pdf);\n",
    "print(bin_edges)\n",
    "\n",
    "#compute CDF\n",
    "cdf = np.cumsum(pdf)\n",
    "plt.plot(bin_edges[1:], pdf)\n",
    "plt.plot(bin_edges[1:], cdf)\n",
    "plt.xlabel('Axil_nodes')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Boxplot and Whiskers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='survived_status',y='nodes', data=haberman_dataset_cleaned)\n",
    "plt.title(\"BOX PLOT AND WHISKERS FOR SURVIVE AND DIDNT SURVIVE\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Box plot shows that, the more number of axil nodes, the more patients likely to die\n",
    "\n",
    "The patients who had axil nodes from 1 to 24 are the majority of patients who died."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Violon Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x='survived_status',y='nodes', data=haberman_dataset_cleaned, size=8)\n",
    "plt.title(\"VIOLIN PLOT FOR SURVIVE AND DIDNT SURVIVE\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "After taking a look at violin plot we can see that, the large number of patients who survived had 0 axil nodes or doesn't had it at all.\n",
    "\n",
    "Patients and who died had axil node greater than or equal to 1, and as the concentration of axil node increases the repective patient is more likely to die."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multivariate Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x= 'age',kind = 'kde', y='operation_year', data = haberman_dataset_cleaned)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "There are more number of patients undergone operation during the year 1960 - 1964 period and between ages 45 - 55"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x= 'age',kind = 'kde', y='nodes', data = haberman_dataset_cleaned)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Conclusion:::"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "1. Axil_nodes is most important feature in this dataset, as who had Axil node >= 1 those are more likely to die.\n",
    "\n",
    "2. Age is also somewhat important feature of this dataset, because we have seen that patients who aged less \n",
    "than 40 are likely to survive inspite of having axil node >= 1\n",
    "\n",
    "3. From this Dataset we can say that the majority of operations are performed on people age range between 38 and 68, \n",
    "where most of the points plotted on scatter plot (Operation_year vs Age)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Building of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1e94c13bd30>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VSQAAADfxrG0AAACgBKhIAgAAuIl9JAEAAIASoCIJAADgLvaRBAAAAFxHRRIAAMBNFXWOJIkkAACAu9j+BwAAAHAdFUkAAAA3WSwVc2ibiiQAAABKhYokAACAu5gjCQAAALiOiiQAAICbKur2P1QkAQAAUCpUJAEAANzFIxIBAAAA11GRBAAAcBdzJAEAAADXUZEEAABwk6WCzpEs00SyZdLbZXk5lAM7mvf2dAjwQk2T13g6BHihPGugp0MA8AdUJAEAANzFHEkAAADAdVQkAQAA3GThWdsAAACA66hIAgAAuMvCHEkAAADAZVQkAQAA3FVB50iSSAIAALiLoW0AAADAdVQkAQAA3MT2PwAAAEAJUJEEAABwl6Vi1uYqZq8BAADgNiqSAAAA7rKyahsAAABwGRVJAAAAN1mYIwkAAAC4jookAACAu5gjCQAAALiOiiQAAIC7mCMJAACA8u6TTz7Rvffeq44dO2rZsmWXbPfVV1+pQ4cObl2LiiQAAIC7LN4xR/LkyZOaPn26PvroI/n5+enhhx9W69atFRERUahdenq6Jk2a5Pb1qEgCAABcIbZs2aLIyEhVr15dAQEBuvvuu7V27doi7caMGaPo6Gi3r0dFEgAAwF1Wc2tz2dnZys7OLnI+KChIQUFBzuPU1FSFhIQ4j0NDQ5WUlFToM4mJifrrX/+qG2+80e24SCQBAAC8XEJCguLi4oqcj46O1qBBg5zHDodDlt8NsxuGUej4wIEDWr9+vRYvXqwTJ064HReJJAAAgLtMXrXdt29fde3atcj531cjJSksLEw7duxwHqelpSk0NNR5vHbtWqWlpal79+4qKChQamqqevfurbfffrtUcZFIAgAAeLk/DmFfStu2bfXmm28qIyNDlStX1vr16zVhwgTn+zExMYqJiZEkpaSkKCoqqtRJpMRiGwAAAPdZLea+XFSrVi0NHTpUUVFR6tKli+677z41b95c/fv31549ey57ty2GYRiX/Vsv4eS+nWV1KZQTO5r39nQI8EJNk9d4OgQA5UR4w4aeDkGSdG5l0fmLl5P/g+6vsDYDFUkAAACUCnMkAQAA3OUlG5KXNSqSAAAAKBUqkgAAAO4yeUNyb1Uxew0AAAC3UZEEAABwF3MkAQAAANdRkQQAAHCXyY9I9FYVs9cAAABwGxVJAAAAd7FqGwAAAHAdFUkAAAB3sWobAAAAcB0VSQAAAHexahsAAABwHRVJAAAAdzFHEgAAAHAdFUkAAAB3sY8kAAAA4DoqkgAAAG4ymCMJAAAAuI6KJAAAgLsq6D6SJJIAAADuqqCJZMXsNQAAANxGRRIAAMBNLLYBAAAASoCKJAAAgLsq6BxJEsnL7Nsd32vOkndVUGBTeP1rNTL6SVUJCHCpTfaZHE17a6F+/vU3+ftfpXs73K7u993toZ7AE25c+LrO7Dmgg9MXejoUXEbbtm3T4kWLVFBQoAYNGmjIkCEKqFLF5XZ2u13z583Tzp07Zbfb1a17d3Xu3FmStHv3bi1YsEB2m01+fn56auBANWnSRJK0evVqrVq5UlarVWFhYRo8ZIiqVatWpn3HpZl5X/zXiRMnFDNokF559VU1btxYEvcFLq+KmT6bJDMrWxPfnKMJI4do2axpql2rluYkvutymzcXLlFlf38lvjlFb00ar+92/aAt23d5oisoY4FNG6r1+gSFdeMXhytNVmampsfGavSYMZo3f77CwsK0aNGiErVbs2aNjh49qtlvvaUZM2dq5YoVSk5OVkFBgV6fOFGDY2IUP2uWHu7VS1OnTJF0IYFITEjQ5ClTNGv2bIXWqqWlS5eWad9xaWbeF/+Vn5+vKVOmyGazOc9xX5jIYjH35aVcSiRHjRpldhxXhG0/JKlpRENdW6e2JKnLPXfq803fyDAMl9oc+OVX3d3+Vvn4WOXrW0ltWv5NX23Z5pG+oGzVG/iIjixcruMfrvV0KLjMdu3apcaNG6tu3bqSpM733aeNGzcW+rnwZ+22bNmiuzp2lI+Pj6pWrap2t9+ujV9+KV9fXy1ZulThEREyDEMnTpxQUFCQJMnhcMhmsykvL08Oh0Pnz5+Xn59f2XYel2TmffFfs+LjddeddzrvCYn7ApefS0PbBw4c0NmzZ1XlIiV3/E9qeoZCg692HocE19TZ3Dzl5uU5h7eLa3Ndowit+2qzml3XWPkFNn397TZV8vEp836g7O0dPEGSFHzXLR6OBJdbWnq6gkNCnMfBwcHKzc1VXm5uoWHM4tqlp6UpJDi40HuHfv1VklSpUiWdPn1aMYMGKSsrS8//5xf/OnXqqHuPHurfr58CAwMVUKWKYmNjze4uXGT2fbF27VrZ7Hbd06mT3n33fyNj3BcmslbMQV6XEkmr1ao77rhDDRo00FVXXeU8n5iYaFpg5ZHhcFy0+mz93c1VXJtn/u8RzVq8TE88+4JqVq+mm29spn/vP2BixADMZjgcutiglPUPvyQW185hGIWHtgyj0M+VGjVqaMnSpfr555/1wqhR+stf/qLUkyf1zebNSlyyREFBQVq0cKFip03TuJdfvjwdg1vMvC9+/vlnrV69WpMnTy7yuV07d3Jf4LJyKZEcMWKE2XFcEWqFBOvHn35xHqefylDVwCqq7O/vUpuTaeka2Le3gqoGSpKWLF+hurXDyq4DAC6LJYmJ2rp1qyQpNzdX9evXd76Xnp6uwMBA+f/u54IkhYSGFprf9vt2oSEhyjh1yvneqYwMBQcH6+zZs9r9ww9qe8uFSnZERIQaNGigQ4cOKSkpSZGRkapevbok6b7779fAp54yq8twQVndFxu++EK5ubkaPmyYJCkjI0NTJk/WE/36adeuXdwXJmEfyWK0atVKgYGBslqtslgscjgcOnz4sNmxlTs339RMPyb/pCPHjkuSVq7boFtb/d3lNivXfqEF7yyXJGVkZunTLzbqznZty7AHAC6HPlFRiouPV1x8vGKnT9f+/ft19OhRSRdWzEa2aVPkMy1atLhku8jISK1fv152u105OTna9PXXatOmjaxWq2bMmKG9e/dKkn777TelpKSoaZMmiggP17bt25WXlydJ+mbzZjVt2rQsuo9LKKv7YsBTT2n+/PnOa9WsWVMjnntOkZGR3Be47CzGH2f2XsSYMWO0bds2ZWVlqWHDhtq/f79atGihBQsWlOhiJ/ftLHWg5cW3O77X3KXvqcBmU92wWho9eKCOnUzV5Lh5Wjhj4iXbBFUNVG5enl6ZPktHT5yUYRh6tPuD6tj+Vg/3yFw7mvf2dAhepfmCicr5908VfvufpslrPB3CZbV92zYtXrxYNptNYbVra/jw4apataoOHDigN2bOVFx8fLHt/rvNy/fffy+bzaZOnTqpe48ekqQ9SUmaP3++7Ha7Kvn66rHHHtNNN90kwzC0dMkSbdq0Sb6+vgoNDVV0dHSh+XbwLDPvi997rG9fvTB6tBo3bnxF3hfhDRt6OgRJ0tlvV5j6/VXadDH1+0vLpUSyQ4cOWrdunSZMmKCoqCjl5eXp9ddf17Jly0p0sYqQSKJkSCRxMVdaIgnAPCSSnuXSHMnQ0FD5+voqPDxcycnJ6ty5s86cOWN2bAAAAOWCwZNtLq1WrVqaM2eO2rRpoyn/2ew2Pz/f1MAAAADg3VxKn1999VVdc801at68uTp27KhPP/1U48aNMzk0AACAcqKCPtnGpYpkYGCgbrzxRn311Vfq1auX2rdvr2uvvdbs2AAAAODFXKpIrl69WgMHDtQrr7yirKwsPfzww1q5cqXZsQEAAJQLhsVq6stbuRTZvHnz9M477ygwMFBXX321Pv74Y82dO9fs2AAAAODFXH5EYmBgoPM4NDS00OO5AAAAKjQvnsdoJpcSyUaNGmnp0qWy2Wzat2+f3n77bXbCBwAA+C8vHn42k0u9fvHFF3Xy5EldddVVeuGFFxQYGKiXXnrJ7NgAAADgxVyqSL799tuKiorSsP88AB4AAAD/Y1TQoW2XKpLnzp1Tnz599OSTT2rNmjUqKCgwOy4AAAB4OZcSyejoaK1du1ZPPvmktm7dqgcffFDjx4/Xvn37zI4PAADA+1ms5r68lMuR5ebmKiUlRUeOHJHValW1atX06quvatq0aWbGBwAAAC/l0hzJ4cOH67vvvlO7du00cOBAtWzZUtKF523feuutzJ0EAAAVmqGKOUfSpUQyMjJS48ePV0BAQKHzfn5+euGFF0wJDAAAAN7NpaHtHj16FEki/yshIeGyBgQAAFDe8IjEUjIM43LEAQAAgHLGpaHt4lgq6L5JAAAATl5cNTRTxew1AAAA3OZ2RRIAAKCi48k2pcQcSQAAgIrJpYqkzWbT5s2blZmZWeh8ly5d9N5775kSGAAAQHnhzSurzeRSIjls2DAdO3ZM4eHhhRbXdOnSRVdddZVpwQEAAMB7uZRIJicna+3atWbHAgAAUD4xR/LSwsPDlZqaanYsAAAAKEdcqkieO3dO99xzjxo3biw/Pz/n+cTERNMCAwAAKC+YI1mMAQMGmB0HAAAAyhmX0udWrVopLy9PGzdu1Oeff67s7Gy1atXK7NgAAADKBUMWU1/eyqWK5Lx587R+/Xrdf//9MgxDb731ln766ScNHDjQ7PgAAAC8HkPbxVi1apWWL18uf39/SdJDDz2kbt26kUgCAABUYC4lkoZhOJNISbrqqqtUqRJPVwQAAJBUYbf/cSkbjIyM1KBBg9S1a1dJ0ooVK9S6dWtTAwMAAIB3cymRHD16tN555x2tWLFChmEoMjJSPXv2NDs2AACAcsFwbf3yFafYRDItLU0hISE6fvy42rdvr/bt2zvfS01NVZ06dcyODwAAAF6q2ERyzJgxmjNnjh599NFCz9g2DEMWi0UbNmwwPUAAAABvZzBHsqg5c+ZIkj766CNVr1690HspKSnmRQUAAACvV+yA/vHjx3Xs2DE9+uijzv8+duyYjhw5on79+pVVjAAAAF7NsFhNfXmrYiuSb7zxhrZu3arU1FQ98sgj//tQpUqF5ksCAACg4ik2kZw4caIkae7cuXryySfLJCAAAIDyxpsfY2gml7b/6d69uxYvXqyzZ8/KMAw5HA6lpKRo8uTJZscHAAAAL+XSoPvQoUO1b98+rVq1Snl5eVq3bp2sVu8drwcAAChLFXWOpEuRpaamatKkSerQoYM6duyopUuX6scffzQ7NgAAAHgxlxLJatWqSZIaNGig/fv3q0aNGqYGBQAAUJ4YFoupL2/l8rO2Y2JiNHLkSD3++OPau3ev/P39zY4NAAAAXsylRLJv377KyclR3bp1FRsbq+3bt+uZZ54xOzYAAIBygVXbxXjkkUe0Zs0aSdL111+v66+/3tSgAAAA4P1cSiSbNm2qFStWqHnz5oWGtOvUqWNaYAAAAOWFN6+sNpNLieTu3bu1e/fuQucsFos2bNhgSlAAAADwfi4lkl9++aXZcQAAAJRbFXWOpEt12KysLI0ZM0ZRUVHKzMzUqFGjlJ2dbXZsAAAA5QIbkhdj7NixatasmTIzMxUQEKDQ0FANHz7c7NgAAADgxVxKJFNSUtSzZ09ZrVb5+flp6NChOnHihNmxAQAAlAuGLKa+vJVLiaSPj4/OnDkjy392Vj906BDP2gYAAKjgXMoGY2Ji1KdPHx07dkxPP/20evfurSFDhpgdGwAAQLngTXMkP/nkE917773q2LGjli1bVuT9ffv2qVu3brr77rs1evRo2Wy2UvfbpVXbt912m66//nolJSXJ4XBo/PjxCg4OLvVFAQAAcPmdPHlS06dP10cffSQ/Pz89/PDDat26tSIiIpxtRowYoVdeeUU33XSTXnjhBb3//vvq3bt3qa7nUoqbnZ2t2bNna9q0aXrzzTe1ZMkSnTt3rlQXBAAAuNJ4yxzJLVu2KDIyUtWrV1dAQIDuvvturV271vn+0aNHde7cOd10002SpG7duhV6v6RcqkiOGDFCDRs21NSpU2UYhj788EONHj1a06ZNK9HF0n15Eg4Ka5q8xtMhwAvtb9LJ0yHAC3X4fJynQ4A3atjQ0xGUiezs7ItuvRgUFKSgoCDncWpqqkJCQpzHoaGhSkpKuuT7ISEhOnnyZKnjcimRPHr0qObMmeM8HqCyaTMAACAASURBVD16tO67775SXxQAAOBKYljMXVmdkJCguLi4Iuejo6M1aNAg57HD4XAujpYkwzAKHf/Z+yXlUiIZERGhHTt2qGXLlpKk/fv3q169eqW+KAAAAFzXt29fde3atcj531cjJSksLEw7duxwHqelpSk0NLTQ+2lpac7j9PT0Qu+XlEuJ5MGDB9WnTx/Vr19flSpV0q+//qqgoCB16NCBZ24DAIAKzzDMrUj+cQj7Utq2bas333xTGRkZqly5stavX68JEyY4369bt66uuuoq7dy5U3//+9+1cuVKtWvXrtRxuZRIxsfHa9OmTfruu+9ks9nUo0cP3XHHHfLx8Sn1hQEAAHB51apVS0OHDlVUVJQKCgrUo0cPNW/eXP3791dMTIyaNWumqVOnasyYMcrJydH111+vqKioUl/PYhiG8WeNJk2apMOHD6tbt24yDEMfffSR6tatq9GjR5foYnt/Pl7qQHFl8rfmeToEeCEW2+BiWGyDi6ncvpenQ5Ak/fTLb6Z+f6Nw75xS6FJF8ptvvtGKFSucT7Np37697r//flMDAwAAgHdzKZG02+2y2Wzy8/NzHjOsDQAAcIE3Pw/bTC4lkvfff7+ioqLUuXNnSdJnn33G9j8AAAAVnEuJ5FNPPaW//vWv+vbbb2UYhp566im1b9/e5NAAAADKByqSf6Jdu3ZuLQ8HAADAlcXlRBIAAAAXV1ErklZPBwAAAIDyiYokAACAm6hIAgAAACVARRIAAMBNZj9r21uRSAIAALiJoW0AAACgBKhIAgAAuImKJAAAAFACVCQBAADcREUSAAAAKAEqkgAAAG6qqNv/UJEEAABAqVCRBAAAcJODOZIAAACA66hIAgAAuIlV2wAAAEAJUJEEAABwE6u2AQAAgBKgIgkAAOAm5kgCAAAAJUBFEgAAwE3MkQQAAABKgIokAACAm5gjCQAAAJQAFUkAAAA3VdQ5kiSSAAAAbnJ4OgAPYWgbAAAApUJFEgAAwE0VdWibiiQAAABKhYokAACAm9j+BwAAACgBKpIAAABuYo4kAAAAUAJUJAEAANzEHEkAAACgBKhIAgAAuMlheDoCz6AiCQAAgFKhIgkAAOAm5kgCAAAAJUBFEgAAwE3sIwkAAACUABVJAAAANxms2gYAAABcR0USAADATQ5WbQMAAACuoyJ5GezY9q2WJcxTQUGB6tVvqGeGPKeAgColarfm0xX6Yv1nyj9/XuERjfXMkOfk6+unPbu/V+LC2bLZ7fLz81O/ATFq1OS6su4iXLRt2zYtXrRIBQUFatCggYYMGaKAKkXvhUu1s9vtmj9vnnbu3Cm73a5u3burc+fOkqTdu3drwYIFstts8vPz01MDB6pJkyaSpNWrV2vVypWyWq0KCwvT4CFDVK1atTLtO8xz48LXdWbPAR2cvtDTocBkm/Yc0Jsff6F8m12N6tbSuKgHFFjZv1Cbz77brYTPt0iS/P18NbJnJ11fv66yzubq1WWfKTnlhCr7+erBtn9Trw6tPdGNColV2yiVrKxMxc2YpBEvjFfc3CWqFVZHSxbNLVG7777ZpNWffKRxr07TzNmLlZ+fr08+Xq6CggJNm/SyBsaM0PS4Bfrnw300c9prZd1FuCgrM1PTY2M1eswYzZs/X2FhYVq0aFGJ2q1Zs0ZHjx7V7Lfe0oyZM7VyxQolJyeroKBAr0+cqMExMYqfNUsP9+qlqVOmSJJOnDihxIQETZ4yRbNmz1ZorVpaunRpmfYd5ghs2lCt1ycorNvdng4FZSDjzFm9lLBCUwf01Mrxg3RNcA3N/PiLQm0OnUjX9A8/V3zMo3p/7ED1v7edhr31niRpyvvrFODvp4/GPaMlz/fT5r0/aVNSsie6UiEZhrkvb0Ui6aYfdm1XRKOmqlP3GknSPZ0f0L+++kLGH/7Ui2v31Zfr9EC3h1S1apCsVqsGRD+r2zt0lK+vr+YnfqCG4Y1kGIZOnjiuqlWDyryPcM2uXbvUuHFj1a1bV5LU+b77tHHjxiL3QnHttmzZors6dpSPj4+qVq2qdrffro1ffilfX18tWbpU4RERMgxDJ06cUFDQhXvB4XDIZrMpLy9PDodD58+fl5+fX9l2HqaoN/ARHVm4XMc/XOvpUFAGvv3xF11fr67q1bpakvTP21tqzdY9hX6G+Fby0YtRDyikWlVJ0vX16ig9O0cFNpv2HT6mzq2by8dqlW+lSrrthsb6fNePHukLKg6Xh7ZTU1MVGhqqHTt2KDk5Wd27d5e/v/+ff/AKdyotVcEhIc7jq4NDlJt7Vnl5uYWGt4trd+xoiiIyMzV+7Aidzjil665vrqjHB0iSKlWqpMzTGRo++EllZ2Vp2PMvll3nUCJp6emF/oyDg4OVm5urvNzcQsPbxbVLT0tTSHBwofcO/fqrpAv3wunTpxUzaJCysrL0/KhRkqQ6deqoe48e6t+vnwIDAxVQpYpiY2PN7i7KwN7BEyRJwXfd4uFIUBZOns5SWM3/FQtq1QhSzrnzOnvuvHN4u25wDdUNriFJMgxDU5evU/sbm8i3UiU1a3CNPtuapJsi/qKCAps2fP+jKvn4eKQvFRGPSCzGSy+9pBkzZujnn3/WsGHDtHfvXo0ZM8bs2MoFh2HIYil681itVpfb2e02JX2/Q8NHjdPkGXOUcyZbyxLnO9tUr1FT8xM/0MRp8YqbPknHjh65/B2B2wzHxdfsWf/wg7y4dg7DkH5/nxhGoXupRo0aWrJ0qWKnT9eM6dOVkpKiXTt36pvNm5W4ZImWLlumNpGRip027fJ0CkCZcTgMWS7y08HHWvSf6rzz+Roxd7mOpGXoxT4PSJKe7dFRFkkPv/KWhs5+V5HXhcuXRBImc6kiuWfPHn344YeKi4tTjx49NGjQIHXv3t3s2LzWO0sWavvWbyRJebm5+kv9hs73Tp1KV2BgVfn7Vy70mZCQUP2UvO+i7WrUDFbrtu2cFcx2d9yl5e8k6uzZHO3Z/b0i294mSQqPaKz6DcP126GDqlP3WrO7CRcsSUzU1q1bJUm5ubmqX7++87309HQFBgYWqdyHhIYqOTn5ou1CQ0KUceqU871TGRkKDg7W2bNntfuHH9T2lguVqYiICDVo0ECHDh1SUlKSIiMjVb16dUnSffffr4FPPWVWlwGYpHbNavr3oaPO49TMMwoK8FflqwpPVTmekanB8e+oQViw5j37mPz9fCVJZ8+d15Dud6lalQBJ0vzVm3RtaM2y60AF5/DieYxmcqkiabfb5XA4tGHDBrVr1055eXnKy8szOzav1avP44qNW6DYuAWaGDtLB5J/1LGjKZKk9atX6ebIosNQN7a4+ZLt2txyu7Zs3qjz58/LMAxt+26zIho3kdVqVfyMSdr34x5J0uHfftXRI4dZte1F+kRFKS4+XnHx8YqdPl379+/X0aMX/iFYvXq1Itu0KfKZFi1aXLJdZGSk1q9fL7vdrpycHG36+mu1adNGVqtVM2bM0N69eyVJv/32m1JSUtS0SRNFhIdr2/btzr+T32zerKZNm5ZF9wFcRm3+Gq6kgyn67eSFXyY/2LRD7W8s/Hf57Lnz6jdtsTrcdJ0m9f+nM4mUpOVf79CsVRslSaeyc/TxN7vUqVWzsusAKiSL8ceVABexaNEizZ07Vy1atFB8fLzuvfde9ezZU3379i3Rxfb+fLzUgXqzndu/09KEebIVFCisdh3FDHtBVasG6eef9mvWzCmKjVtQbDu73a4P3luibzZtlMPhUMPwRnpq0DAFBFTR3j0/aPGC2bLbbPL19dOjj/VXsxtbeLjHl4+/9cr6hWT7tm1avHixbDabwmrX1vDhw1W1alUdOHBAb8ycqbj4+GLb/Xf7n++//142m02dOnVS9x49JEl7kpI0f/582e12VfL11WOPPaabbrpJhmFo6ZIl2rRpk3x9fRUaGqro6OhC8zDLm/1NOnk6BK/SfMFE5fz7pwq//U+Hz8d5OgTT/WvPAb25YoMKbHZdE1JDr/xfV6WkndbLS1bp/bEDtWDNvxS/8ktF1A0t9Lm5Q/vKt5KPRi/8SEfSMmQY0hP33KrOkTd6qCdlp3L7Xp4OQZK05vsCU7+/0998/7yRB7iUSEoXVob+d65WRkaGatYsebn8Sk0kUXpXWiKJy4NEEhdTERJJlByJpGe5NLR99OhRPfHEE+rYsaNSU1M1ZMgQpaSkmB0bAABAucA+ksV48cUX9cQTTyggIEAhISG67777NHLkSLNjAwAAgBdzKZE8ffq0br31VkmSxWLRQw89pJycHFMDAwAAKC8cspj68lYuJZL+/v46ceKEcx/EHTt28OQMAACACs6lfSSff/55DRgwQIcPH9aDDz6orKwszZgxw+zYAAAAygVvnsdoJpcSyebNm+uDDz7QoUOHZLfb1bBhQyqSAAAAFVyxieSo/zzL91ImTpx4WYMBAAAojwzDe+cxmqnYOZKtWrVSq1atdPbsWaWmpioyMlK33nqrsrOz5eL2kwAAALhCFVuR7Nq1qyTp7bff1nvvvefckLxTp0566KGHzI8OAACgHOBZ28U4c+aMMjMzncfp6enKzc01LSgAAAB4P5cW2zz11FN64IEH1KJFCxmGoR9++EFjx441OzYAAIByoaLO+HMpkezSpYvatm2r77//XlarVePGjdPVV19tdmwAAADwYi4lknl5eUpISNC3334ru92uyMhIDR48WAEBAWbHBwAA4PUML376jJlcmiM5fvx45eXl6bXXXtOkSZNUUFCgl156yezYAAAAygWHYe7LW7lUkdy7d69WrVrlPH7xxRd17733mhYUAAAAvJ9LiaRhGMrOzlZQUJAkKTs7Wz4+PqYGBgAAUF6w2KYYjz32mP75z3/qjjvukGEY2rhxo5588kmzYwMAAIAXcymRfOCBB5SXl6esrCxVq1ZNffr0UaVKLn0UAADgikdFshjDhw/XsWPHFB4erpSUFOf5Ll26mBYYAAAAvJtLiWRycrLWrl1rdiwAAADlksNg+59LCg8PV2pqqtmxAAAAoBxxqSJ57tw53XPPPWrcuLH8/Pyc5xMTE00LDAAAoLxgjmQxBgwYYHYcAAAAKGdcSiRbtWpldhwAAADlVkWtSLo0RxIAAAD4IzaDBAAAcJM3Pw/bTFQkAQAAUCpUJAEAANxksI8kAAAA4DoSSQAAADcZhrkvdx07dkyPPPKI7rnnHg0cOFBnz569ZNucnBzdeeed2rp1659+L4kkAADAFe7ll19W7969tXbtWt1www2aNWvWJdtOmDBB2dnZLn0viSQAAICbHIa5r+zsbKWkpBR5uZLwFRQUaPv27br77rslSd26ddPatWsv2nb16tWqUqWKmjRp4lK/WWwDAADg5RISEhQXF1fkfHR0tAYNGlTsZ0+fPq3AwEBVqnQh7QsJCdHJkyeLtDt27JgSEhKUkJCg/v37uxQXiSQAAICbzH6yTd++fdW1a9ci54OCggodr1mzRhMnTix0rl69erJYCq8q/+Oxw+HQ6NGjNXbsWPn7+7scF4kkAACAlwsKCiqSNF5Mp06d1KlTp0LnCgoK1Lp1a9ntdvn4+CgtLU2hoaGF2hw8eFAHDx7U6NGjJUmHDx/WmDFjNGHCBEVGRl7yeiSSAAAAbvLmZ237+vqqZcuWWr16te6//36tWLFC7dq1K9QmIiJCX3/9tfO4T58+io6OVuvWrYv9bhbbAAAAuMnsxTbueumll/T+++/r3nvv1Y4dOzRkyBBJ0jvvvKOZM2eW+nupSAIAAFzh6tatqyVLlhQ536tXr4u2v1jbiyGRBAAAcJM3D22biaFtAAAAlAoVSQAAADc5HJ6OwDOoSAIAAKBUqEgCAAC4iTmSAAAAQAlQkQQAAHATFUkAAACgBKhIAgAAuOlyPH2mPKIiCQAAgFKhIgkAAOAmw/RJkhaTv790qEgCAACgVKhIAgAAuIlV2wAAAEAJUJEEAABwE8/aBgAAAEqAiiQAAICbmCMJAAAAlECZViRr2NPK8nIoB/KsgZ4OAV6ow+fjPB0CvNCXd43zdAjwQp0Lenk6BEkV98k2DG0DAAC4iaFtAAAAoASoSAIAALjJMH1sm0ckAgAA4ApCRRIAAMBNFXWxDRVJAAAAlAoVSQAAADexahsAAAAoASqSAAAAbnJU0EmSVCQBAABQKlQkAQAA3MQcSQAAAKAEqEgCAAC4iYokAAAAUAJUJAEAANzkqKAlSSqSAAAAKBUqkgAAAG4yHJ6OwDOoSAIAAKBUqEgCAAC4yWCOJAAAAOA6KpIAAABuclTQOZIkkgAAAG5iaBsAAAAoASqSAAAAbnJUzIIkFUkAAACUDhVJAAAANxkVtCRJRRIAAAClQkUSAADATRV00TYVSQAAAJQOFUkAAAA3OZgjCQAAALiOiiQAAICbeLINAAAAUAJUJAEAANxkODwdgWdQkQQAAECpUJEEAABwk4M5kgAAAIDrqEgCAAC4iVXbAAAAQAlQkQQAAHATT7YBAAAASoCKJAAAgJsq6BRJEkkAAAB3GQxtAwAAAK6jIgkAAOAmNiQHAAAASoCKJAAAgJuYIwkAAACUABVJAAAAN1GRBAAAAEqAiiQAAICbKmhBkookAAAASoeKJAAAgJuYIwkAAACUABVJAAAANxk82QYAAABwHRVJN327fafmJ76tAluBGtarpxExA1UlIMDlNitWr9Pq9Rt0Pj9fjcMbakTMQPn5+urQ4SOaFj9HeefOySKL+vd9RK1a3OSJLqIEtm3bpsWLFqmgoEANGjTQkCFDFFClisvt7Ha75s+bp507d8put6tb9+7q3Llzoc+eOHFCMYMG6ZVXX1Xjxo0lSatXr9aqlStltVoVFhamwUOGqFq1amXSZ5TOpj0H9ObHXyjfZlejurU0LuoBBVb2L9Tms+92K+HzLZIkfz9fjezZSdfXr6uss7l6ddlnSk45ocp+vnqw7d/Uq0NrT3QDHnLjwtd1Zs8BHZy+0NOh4D8czJFESWVmZWnyG7P08qjhSpz9hmqH1dLchGUut9m0Zas+/nSNpk4Yq0VxsTqfn68PVn4qSZrx1nx1urOD5s+cqudintb4ybGy2+1l3ke4LiszU9NjYzV6zBjNmz9fYWFhWrRoUYnarVmzRkePHtXst97SjJkztXLFCiUnJzs/m5+frylTpshmsznPnThxQokJCZo8ZYpmzZ6t0Fq1tHTpUvM7jFLLOHNWLyWs0NQBPbVy/CBdE1xDMz/+olCbQyfSNf3DzxUf86jeHztQ/e9tp2FvvSdJmvL+OgX4++mjcc9oyfP9tHnvT9qUlHyxS+EKE9i0oVqvT1BYt7s9HQogiUTSLdu/T1KTRuG6pk5tSdKDnTpqw9f/KjRPorg26zd+rYe63K+gqlVltVr17NP9ddcd7SRJDodDOTlnJUm5eXny8/Ur496hpHbt2qXGjRurbt26kqTO992njRs3Fpk3U1y7LVu26K6OHeXj46OqVauq3e23a+OXXzo/Oys+XnfdeaeCgoKc5xwOh2w2m/Ly8uRwOHT+/Hn5+XG/eLNvf/xF19erq3q1rpYk/fP2llqzdU+he8W3ko9ejHpAIdWqSpKur1dH6dk5KrDZtO/wMXVu3Vw+Vqt8K1XSbTc01ue7fvRIX1C26g18REcWLtfxD9d6OhT8gWEYpr68FUPbbkhLT1docLDzOCT4ap3NzVNuXp5z6Lq4NinHjul0ZoSee+kVnco4rWbXX6cBjz0qSRo8oJ+eHfOylq/6VJlZWRo7fKh8fHzKtoMokbT0dAWHhDiPg4ODlZubq7zc3ELD28W1S09LU8jv7pfg4GAd+vVXSdLatWtls9t1T6dOevfdd51t6tSpo+49eqh/v34KDAxUQJUqio2NNbOrcNPJ01kKq/m/XwZq1QhSzrnzOnvuvHN4u25wDdUNriHpwj9QU5evU/sbm8i3UiU1a3CNPtuapJsi/qKCAps2fP+jKvHzoULYO3iCJCn4rls8HAlwgUsVyaSkJC1atEj5+fl6/PHHFRkZqU2bNpkdm9dzOAxZLnLearW61MZms2vn7iS9NPJZvRX7us6cydGCJe8oPz9f46dM1/NDntHyRXM087Xxip01R6lp6ab1Be4zHI6L/1n/4R/44to5DEOy/O5dw5DVatXPP/+s1atXKzo6usjndu3cqW82b1bikiVaumyZ2kRGKnbaNPc6A1Nd+LlQ9C7wsRb9kZx3Pl8j5i7XkbQMvdjnAUnSsz06yiLp4Vfe0tDZ7yryunD5kkgCHmU4DFNf3sqliuQrr7yimJgYrVu3Tv7+/vr4448VHR2tdu3amR2fV6sVEqx9B35yHqedylDVwCqq7O/vUpura9bQbW1aO6uXd7a/TYnvfaBffzui8+fPq83Nf5ck/bVpY9X/y7Xad+AnhYb8r1oFz1uSmKitW7dKknJzc1W/fn3ne+np6QoMDJS/f+EFFCGhoYXmPf6+XWhIiDJOnXK+dyojQ8HBwdrwxRfKzc3V8GHDJEkZGRmaMnmynujXT7t27VJkZKSqV68uSbrv/vs18KmnzOoyLoPaNavp34eOOo9TM88oKMBfla8qPCXheEamBse/owZhwZr37GPy9/OVJJ09d15Dut+lalUu/OyYv3qTrg2tWXYdAID/cKki6XA4dOutt+qrr75Sx44dVbt2bRZ+SGr5txu1L/knpRw7Lkn6ZM163dL6Zpfb3H5LG321eYvOnz8vwzD0zdbtahoRrrq1w5STm6t/77uQbBw9fkK/HUlRRMMGZdg7uKJPVJTi4uMVFx+v2OnTtX//fh09eiFBWL16tSLbtCnymRYtWlyyXWRkpNavXy+73a6cnBxt+vprtWnTRgOeekrz5893XqtmzZoa8dxzioyMVER4uLZt3668vDxJ0jebN6tp06Zl9H8ApdHmr+FKOpii305e+KXhg0071P7Gwn9mZ8+dV79pi9Xhpus0qf8/nUmkJC3/eodmrdooSTqVnaOPv9mlTq2alV0HABRBRbIYlStX1sKFC/Xdd9/pxRdfVGJioqpcZEuTiqZG9Wp6bvDTeun1abLZbKoTVkujhkYr+adfNCVutubPnHrJNtKFhTdnzuRowLMj5XA41KhhQw185klVCQjQhFEjFDdvkfIL8uVj9dGwZwaobu0wD/cYxalevbqGDh2q1159VTabTWG1a2v48OGSpAMHDuiNmTMVFx9fbLvO992n48eP65mnn5bNZlOnTp3UrHnzYq97V8eOOnnypGIGDZKvr69CQ0P17LPPmt5flF7NoEC93PdBjZj7vgpsdl0TUkOv/F9X7T10VC8vWaX3xw7Uuxu36fipLH35wz59+cM+52fnDu2rJzrdptELP1L3l+NlGNLT99+hG+rX9WCPAFRUFsOFpUAnT57U8uXL1bZtW7Vo0UJTpkxRVFSUatWqVaKLHUtOKnWguDLl+QZ6OgR4oTqHt3o6BHihL+8a5+kQ4IU6F3jH1lePjTtp6vcvHleynKusuFSRPHz4sFq3bi273a7t27erffv2Onz4cIkTSQAAgCuRNw8/m8mlRPKNN95w/rfNZlNycrJatmypm2++uZhPAQAA4ErmUiK5ZMmSQsdHjhzRxIkTTQkIAACgvPHmTcPNVKon21x77bU6ePDg5Y4FAAAA5YhLFclRo0YVOv7ll1/UuHFjUwICAAAobxzMkby0Vq1aOf/bYrHonnvuUdu2bU0LCgAAAJfPsWPHNGLECJ06dUoNGjTQ1KlTi2zlmJ+fr1GjRunAgQOyWq0aOXLkn+Z7Lg1tp6amqmvXruratau6dOmi22+/XW+++WbpewMAAHAF8fYNyV9++WX17t1ba9eu1Q033KBZs2YVabNy5Uo5HA598sknmjx5sp5//vk//d5iK5JTp07VqVOn9OWXX+rQoUPO83a7Xbt372bTYwAAgDKQnZ2t7OzsIueDgoIUFBRU7GcLCgq0fft2xcfHS5K6deumRx99VCNGjCjUzuFwKC8vT3a7XXl5eUUe8XsxxSaSHTt21C+//KLvvvuu0PC2j4+Pnn766T/9cgAAgIrA7FXbCQkJiouLK3I+OjpagwYNKvazp0+fVmBgoCpVupD2hYSE6OTJohuod+3aVR9//LFuu+02ZWdnKzY29k/jKjaRbN68uZo3b64777xTVatWdZ43DEMpKSl/+uX/3969R0Vx3m8AfxaiiKwa1EgrgmCimEMVUZEQUQENKXIJuG7RAEJaoRrBWkURjiZ4QWPwclyNBtPWBlEMFAWp2IIQQ48F1Bpq7CFeEjl4WSCGgoICe3l/f3jcXxXZrJeVRZ7POXPOMjsz+8wMC995Z+YdIiIiInp6kZGRCAkJ6TD+4dbIY8eOdeiicfjw4ZBIJA+Me/hnANi5cyfGjRuHzMxMVFdXIyoqCs7OzrC17fwRrAbdbFNQUIBNmzbh7t27unG2trY4fvy4IbMTERERvdCEVmvU5RtyChsA/Pz84Ofn98A4lUqle0Khubk5fvjhBwwZMqTDvMXFxdi2bRskEgkcHR3h4uKCc+fO6S0kDbrZJi0tDXl5eZg5cyaKioqwatUquLi4GDIrEREREXWhXr16YeLEiSgoKAAA5ObmYurUqR2mGz16tK6RsKGhAefPn8frr7+ud9kGFZKDBg2CnZ0dnJyccPHiRYSFheHCBdN4SDoRERFRV9NqhVGHp/Xhhx8iKysLM2fOxJkzZ7BkyRIAQGZmJrZv3w7gXr/h33zzDfz9/REZGYmlS5fCwcFB73INOrVtaWmJ8vJyODk54fjx4xgzZgxaW1ufbo2IiIiI6LmwtbXt8MhrAJg7d67u9eDBg7F79+7HWq5BLZKrV69GSUkJpkyZgsbGRvj5+SE8PPyxPoiIiIjoRSWEMOpgqgxqkayvr0dSUhIA6DoiLywsNF4qIiIiIjJ5egvJgoICtLe3Q6FQYPHixbrxarUaaWlputWznAAAEitJREFU8PX1NXpAIiIiIlP3LJ4+0x3pLSRbWlpw9uxZtLS0oKKiQjfe3Nwcv//9740ejoiIiIhMl95CUi6XQy6Xo6ysDB4eHrrxzc3NkEqlRg9HRERE1B301BZJg262uXv3LlJTU9HS0gI/Pz9Mnz4dhw4dMnY2IiIiIjJhBhWSn3zyCQIDA1FQUICxY8eipKQEGRkZxs5GRERE1C1ohdaog6kyqJAE7vV2fuLECfj4+MDKygoqlcqYuYiIiIi6DaEVRh1MlUGF5ODBg7Fu3TqcP38eU6ZMwUcffYShQ4caOxsRERERmTCDCsktW7ZgzJgxSE9PR9++fWFnZ4ctW7YAAP7zn/8YNSARERGRqWOLpB5SqRTBwcEYPnw4ACAsLEx31/aqVauMl46IiIiITJZBT7bRx5Qf20NERET0PPTUesjgm206I5FInkUOIiIiIupmnrpFkoiIiKin02pNt4seY3rqFkkiIiIi6pl4jSQRERHRUzLlO6uNSW8hefr0ab0zu7m5YceOHc80EBERERF1D3oLSYVCAQBobGxETU0Nxo8fDzMzM3z99dcYNWoUDh48CDs7u+cSlIiIiMhUCRN+jKEx6S0k9+3bBwCIjo7Gzp07df1IXr9+HR988IHx0xERERGRyTLoGskbN27oikgAGDp0KG7cuGG0UERERETdCa+R1MPZ2RkJCQnw8/ODEAL5+fmYOHGisbMRERERkQkzqJBcv349MjIycPDgQQDAm2++iXfffdeowYiIiIi6C7ZI6tG7d2/4+vpixIgR8PT0hFKpxEsvsS9zIiIiop7MoA7JCwoKsHDhQqSkpKCpqQlz5sxBXl6esbMRERERdQtaoTXqYKoMKiQ/++wzZGZmwsrKCoMGDcLhw4exZ88eY2cjIiIiIhNm0PlpMzMzSKVS3c9DhgyBmRmfrkhEREQE8BpJvUaOHImMjAyo1WpUVVXhwIEDGD16tLGzEREREZEJM6hZ8YMPPkBdXR0sLCyQlJQEqVSKDz/80NjZiIiIiLoFodUadTBVBrVIZmdnIyoqCsuWLTN2HiIiIqJup6ee2jaoRbK2thZyuRzz58/HkSNHcPfuXWPnIiIiIiITZ1AhmZCQgJKSEixYsACVlZUIDg7GihUrjJ2NiIiIqFsQQmvUwVQZfOu1EAIqlQoqlQoSiQS9evUyZi4iIiIiMnEGPyKxqKgIr7/+OoKCgrBq1SpYWFgYOxsRERFRt6DtoddIGlRIDh8+HIcPH8bAgQONnYeIiIiIugm9heQXX3yB0NBQNDU14cCBAx3ej42NNVowIiIiou7ClLvoMSa910gK0TObaYmIiIjop+ltkZwzZw4AoF+/fggICMCgQYOeSygiIiKi7oT9SOrBfiSJiIiI6GHsR5KIiIjoKbEfyZ/AfiSJiIiI6H+xH0kiIiKip9RTr5E0qJAcOHAg+5EkIiIiogcYdGo7Pz+fRSQRERFRJ4RWa9TBVEmEAZ1FxsXFwcnJCS4uLujTp49uvJubm1HDEREREZHpMqiQjIiI6DijRIL09HSjhCIiIiIi02dQIUlERERE9DCDbraJiIiARCLpMJ4tkkREREQ9l0GFZFxcnO61Wq1GcXEx+vfvb7RQRERERGT6nvjUtlwuR3Z29rPOQ0RERETdhEEtkjdu3NC9FkLg0qVLaGxsNFooIiIiIjJ9BhWS4eHhkEgkEELAzMwM1tbWWL16tbGzEREREZEJM6hD8m3btiEsLAx/+9vfYG9vj5qaGmPnIiIiIiITZ1AhmZKSglGjRqGwsBB9+vRBbm4utm/fbuxsRERERGTCDCoktVotPD098eWXX8LX1xc///nPodFojJ2N6IWSmJiI69evAwCio6NRV1fXxYmouzh06BBWrlzZ1TGIiDowqJC0tLTEn/70J1RUVMDb2xvp6emwsrIydjaiF0pFRQXud5Lw2WefwcbGposTEVFXyMzMRGZm5lMvJyIiAhUVFY89X1ZWFv7617/qnebcuXNITU190mjUgxh0s83mzZuRnZ0NhUKBAQMGoK6uDlu2bDF2tm5LrVYjOTkZly5dws2bN+Hk5IStW7ciKysLGRkZ6NevH0aMGAF7e3vExcWhtLQUCoUCarUaw4YNw7p162Btbd3Vq9EjfPrppzhy5AjMzc0xefJkvPvuu1i0aBFGjBiBy5cvY+jQoUhNTcXLL7/c6X7y8fHB2LFjUVVVhQMHDiA9PR1lZWVoamrCkCFDsG3bNhw6dAj19fWIiYnB/v37IZPJkJ6ejqFDh2LDhg0oKyuDRCJBUFAQYmJiUFFRgbS0NPTp0wffffcdnJycsHnzZvTu3fuR65GdnY3y8nLd93LHjh2wsLBAWFgY1q5di0uXLkGj0SA6OhoBAQFobm5GUlIS6urqUF9fDw8PD6SkpODUqVNITU2FVqvFyJEjsWnTpue5O15one3T/Px87N27FxKJBM7Ozli9ejWsrKyQm5uL3bt3QyqVwtbWFn379gVw7x/8xo0b0draCmtra6xZswZ2dnbYu3cvDh8+DDMzM4wdOxZr167t4jWmzsydO7dLP//s2bOYNGmS3mkuX76MH3/88Tklom5N0DN36tQpkZycLIQQQqPRiPDwcLFjxw7h6+srbt++LVpbW4VcLhcKhUL8+OOPIigoSDQ2NgohhMjMzBRJSUldGb/HOHHihJDL5eLOnTtCpVKJBQsWiIyMDDFq1ChRXl4uhBBi48aNYt26dXr3k7e3t8jJyRFCCFFdXS1iY2OFRqMRQgixfPly8cc//lE33dWrVx94nZGRId5//32hVqvFnTt3hEwmE19++aUoLy8X48aNE0qlUmg0GiGTyURxcXGn69Lc3Cw8PDzE7du3hRBC+Pr6itraWpGamio+//xzIYQQt2/fFv7+/qKmpkbk5+eLXbt2CSGEaGtrEzNmzBDffPONKC8vFxMmTBC3bt16ptuaxCP3aXp6upgxY4ZoaGgQQgiRnJwsPvroI1FbWysmT54sfvjhB6FSqcSvf/1rkZCQINra2kRgYKC4fv26EEKI0tJSERkZKdRqtXB3dxft7e1Co9GIlStXitra2q5c3ReKUqkUYWFhIiQkRMhkMvH1118/8H0uLy8X4eHhQgghwsPDxaJFi4Svr6/YsWOHWLt2rW45GzduFHv37hUKhUIoFArx+eefP/L95uZmsWLFChESEiKCgoJEfn6+EOLedzU+Pl788pe/FL/5zW+Ev7+/7m/Vo9y+fVtER0eLkJAQERISIo4fPy5Onjwp3NzcxLRp00Rpaam4cOGCCA8PF7NmzRJeXl7iwIEDoqmpSUybNk24ubmJXbt2iZycHJGQkKBbbnh4uCgvL3/kdqGex6AWSXo8bm5uePnll7F//358//33qK6uhru7O7y9vSGVSgEA/v7+uHXrFv79739DqVRi3rx5AO5djzpgwICujN9jlJeXw9/fH5aWlgAAmUyG3NxcODg4wN3dHQAQHByM+Ph4TJ48We9+cnFxAQAMHz4cCQkJyM7OxpUrV1BZWQl7e/tOM1RUVCAkJATm5uawtLREYGAgysrK4OPjg5EjR+JnP/sZAODVV19FU1NTp8uxsrLCtGnTUFRUBDs7O9jZ2cHGxgb//Oc/0draipycHADAnTt3cOnSJQQEBODcuXP485//jO+//x6NjY24c+cOAMDR0RH9+vV70s1Kejxqn3p7e+vOQISGhiIxMREuLi5wdXXF4MGDAQCBgYEoLy9HdXU1rl69ioULF+qW2dzcDHNzc7i6umL27NmYPn063nvvPV468Qz95S9/gZeXF+bPn4/S0lL861//0ju9k5MTdu7ciYaGBgQHByMpKQlmZmYoLCzEF198gYMHDwIAAgICHvn+7t274ezsjE2bNqG5uRlz5syBi4sLCgsLAQDHjh1DdXU1goKC9OYoKiqCra0t9uzZg6qqKhw5cgQJCQnw8fHBpEmTMGXKFKSkpOD999+Hh4cHrl69iqCgIMydOxeLFy/GqVOnsHDhQhw6dMjg7TJu3Lgn2MLUnbGQNILi4mIoFArMmzcPs2bNwn//+1/069cPt27d6jCtRqPB+PHj8emnnwIA2tra0NLS8rwj90harbbDOLVajZde+v+vhRAC5ubmP7mfLCwsAADnz5/HsmXLEBUVhbfffhtmZma66yINySCE0N3Idn+ZAHT9uOojk8mwe/duDBs2DLNmzdItPzU1Fc7OzgCAmzdvYsCAAdi3bx/+/ve/41e/+hXefPNNXLx4Ubf8Pn366P0cenIP79P+/fs/8HdBCAG1Wt1hf9//ndRqtRg2bBjy8vIA3Pv7cfPmTQDArl27UFlZidLSUsyfPx+bN2/+ydOXZBgPDw/ExcWhqqoK06ZNQ3h4OPbv39/p9GPHjgUADBw4EKNHj0ZFRQV69eoFR0dHvPLKK7rpOnu/swPAU6dOITQ0FADg4OAAV1dXvbldXV2xdetW1NXVwcvLC4sWLeowzcqVK/GPf/wDaWlpuHjxou6A8km3C/U8Bt1sQ4+nrKwMfn5+kMlk6N+/v+5i6K+++grNzc1ob29HYWEhJBIJXFxcUFlZiStXrgC498/g448/7sr4PcYbb7yBo0ePorW1FWq1Gjk5OXjjjTdw5coVVFVVAQBycnIwdepUg/fT6dOnMWnSJMydOxcODg44ceKErjC8X5A+nCE3NxcajQZ3795Ffn6+rjX0cU2cOBG1tbWoqKjAjBkzdMu/f1F/fX09goKCoFQqcfLkSYSGhiIoKAhtbW349ttvH1lYk/GVlJTonhSWlZUFd3d3TJgwAZWVlairq4NWq0VBQQEAYMSIEWhqasKZM2cA3Pv9jI+PR0NDA2bOnIlRo0bhd7/7HSZPnowLFy502Tq9aCZMmICjR4/C09MTBQUFWLBgAQDoin21Wv3A9P97MPbOO++goKAABQUFCAwM7LDsR71//wAwLy8PeXl5yMrKwpQpUzo9wOiMg4MDjh07hsDAQJw5cwazZ8/u8D1fsmQJioqK8Oqrr2LJkiWPXM7Dn6tSqfRuF+pZ2CJpBHK5HPHx8Th69Ch69eqF8ePHo6GhAfPmzUNoaCj69u0La2trWFhY4JVXXsGGDRuwZMkSaLVa2NjY8E6558Tb2xtVVVWQyWRQq9Xw9PSEt7c30tLSoFAoUFNTAycnJ6xfvx59+/Y1aD/NnDkTsbGxun8Iv/jFL3Dt2jUAgJeXF2JiYvCHP/xBN31oaCiqq6vxzjvvQKVSITAwEG+99dYT3YkJAG+99RYaGxt1N+XExsYiOTkZAQEB0Gg0WL58Oezt7REZGYnk5GTs2bMHUqkUrq6uuHbtmt7T8PTsSaVS/Pa3v0VERARUKhWcnZ2xZs0aSKVSrFq1ClFRUbC0tMRrr70GAOjduze2b9+OlJQUtLW1QSqVYtOmTRg4cCBCQ0Mxe/ZsWFpawtHRETKZrIvX7sXx8ccfw8bGBpGRkXB3d0dISAiGDRuGy5cvw87ODsXFxZ3OO336dCgUCgghEB8fb9D79w8A169fj/r6egQHB+PgwYPw8PBAfn4+vL29oVQqcfbsWb25MzIycPXqVSQmJmLq1Knw9vbWXQpx/6D25MmTOHbsGGxsbHStrBqNBubm5roC2draGt999x2EELh27ZruIOVR24V6Hon4qfNl9ExcuXIFX331FaKiogAACxcuhFwuh4+PT9cGowdcu3YN8+bNQ0lJSVdHeSxCCKhUKrz33ntISkrSncomoqenVCqxbNkytLS0wNzcHIsXL4ZEIsG6deswYMAAeHp64uzZs9i3bx8iIiIQGxv7wJmFxMREtLe3P9CrAgDExcU98v3m5mYkJyfj22+/hUajQUxMDEJCQqBSqbBmzRqcPn0atra2aGlpwdKlSzs9i9Hc3IylS5dCqVTC3NwcYWFhkMvlOHr0KLZu3Yrly5dDqVQiIyMDFhYWGD16NCorK7F3715otVrExMTg7bffxuLFi7Fs2TJcvHgRjo6OUKvViI6Ohr29fYft4uXlZcQ9QaaIheRz0t7ejsTERFy4cAESiQSenp5YsWIFJBJJV0ej/2HKhWRra6vu+qiHRUVFYcOGDZDL5VixYsVzTkZERD0VC0kiIqJuqqamRtey+bD169djzJgxzzkR9TQsJImIiIjoifCubSIiIiJ6IiwkiYiIiOiJsJAkIiIioifCQpKIiIiInggLSSIiIiJ6Iv8HFFR4ukWHJ8MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize': (12, 9)})\n",
    "sns.heatmap(haberman_dataset.corr(), annot=True, cmap='coolwarm', vmin=-1, vmax=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from matplotlib.ticker import FormatStrFormatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Making the splits inside the datasets:::\n",
    "array = haberman_dataset.values\n",
    "X = array[:,:3]\n",
    "Y = array[:,3]\n",
    "validation_size = 0.30\n",
    "seed = 10\n",
    "X_train, X_validation, Y_train, Y_validation = train_test_split(X, Y, \n",
    "test_size=validation_size, random_state=seed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### for the clarity let us print the splits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[30 64  1]\n",
      " [30 62  3]\n",
      " [30 65  0]\n",
      " [31 59  2]\n",
      " [31 65  4]\n",
      " [33 58 10]\n",
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     ]
    }
   ],
   "source": [
    "print(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Test options and evaluation metric\n",
    "\n",
    "num_folds = 20\n",
    "num_instances = len(X_train)\n",
    "seed = 10\n",
    "scoring = 'accuracy'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Appending the alogorithm and cv_scoring to get the accuracy of all the models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LR: 0.738182 (0.100848)\n",
      "LDA: 0.738182 (0.100848)\n",
      "KNN: 0.710000 (0.121828)\n",
      "CART: 0.602727 (0.110674)\n",
      "NB: 0.747273 (0.099445)\n",
      "SVM: 0.715909 (0.111299)\n",
      "NN: 0.715455 (0.148327)\n",
      "RFC: 0.636364 (0.132490)\n"
     ]
    }
   ],
   "source": [
    "algorithms = []\n",
    "algorithms.append(('LR', LogisticRegression(solver='lbfgs')))\n",
    "algorithms.append(('LDA', LinearDiscriminantAnalysis()))\n",
    "algorithms.append(('KNN', KNeighborsClassifier()))\n",
    "algorithms.append(('CART', DecisionTreeClassifier()))\n",
    "algorithms.append(('NB', GaussianNB()))\n",
    "algorithms.append(('SVM', SVC(gamma='scale')))\n",
    "algorithms.append(('NN', MLPClassifier()))\n",
    "algorithms.append(('RFC', RandomForestClassifier(n_estimators=100)))\n",
    "# evaluate each model in turn\n",
    "results = []\n",
    "names = []\n",
    "for name, algorithm in algorithms:\n",
    "    kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "    cv_results = cross_val_score(algorithm, X_train, Y_train, cv=kfold, scoring=scoring)\n",
    "    results.append(cv_results)\n",
    "    names.append(name)\n",
    "    msg = \"%s: %f (%f)\" % (name, cv_results.mean(), cv_results.std())\n",
    "    print(msg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.782608695652174\n",
      "[[66  6]\n",
      " [14  6]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       0.82      0.92      0.87        72\n",
      "           2       0.50      0.30      0.37        20\n",
      "\n",
      "    accuracy                           0.78        92\n",
      "   macro avg       0.66      0.61      0.62        92\n",
      "weighted avg       0.75      0.78      0.76        92\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Make predictions on validation dataset\n",
    "knn =  GaussianNB()\n",
    "knn.fit(X_train, Y_train)\n",
    "predictions = knn.predict(X_validation)\n",
    "print(accuracy_score(Y_validation, predictions))\n",
    "print(confusion_matrix(Y_validation, predictions))\n",
    "print(classification_report(Y_validation, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>age</th>\n",
       "      <th>operation_year</th>\n",
       "      <th>nodes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30</td>\n",
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      ],
      "text/plain": [
       "    age  operation_year  nodes\n",
       "0    30              65      4\n",
       "1    34              64     10\n",
       "2    35              63     15\n",
       "3    38              64      8\n",
       "4    40              66     40\n",
       "5    50              64     25\n",
       "6    43              64     23\n",
       "7    45              64     40\n",
       "8    34              63      3\n",
       "9    34              63     40\n",
       "10   46              64      3\n",
       "11   50              67      1\n",
       "12   45              64      4\n",
       "13   38              65      2\n",
       "14   42              67      4"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Applying the trained model to unseen data\n",
    "\n",
    "new_data = {'age': [30,34, 35,38,40,50,43,45,34,34,46,50,45,38,42],\n",
    "           'operation_year': [65,64,63,64,66,64,64,64,63,63,64,67,64,65,67],\n",
    "           'nodes': [4,10,15,8,40,25,23,40,3,40,3,1,4,2,4]}\n",
    "final_data = pd.DataFrame(new_data)\n",
    "final_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### After Model Evaluation let's predict the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction of data survival status: [1 1 2 1 2 2 2 2 1 2 1 1 1 1 1]\n"
     ]
    }
   ],
   "source": [
    "prediction = knn.predict(final_data)\n",
    "print(\"Prediction of data survival status: {}\".format(prediction))"
   ]
  }
 ],
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