Telecom_churn_prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "ruled-warning",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import category_encoders as ce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "buried-berry",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Unnamed: 13</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>customerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7590-VHVEG</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5575-GNVDE</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3668-QPYBK</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7795-CFOCW</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9237-HQITU</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2569-WGERO</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>...</td>\n",
       "      <td>No internet service</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>21.15</td>\n",
       "      <td>1419.4</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6840-RESVB</th>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2234-XADUH</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72</td>\n",
       "      <td>Yes</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.9</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4801-JZAZL</th>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8361-LTMKD</th>\n",
       "      <td>Male</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.6</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7042 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            gender  SeniorCitizen Partner Dependents     MultipleLines  \\\n",
       "customerID                                                               \n",
       "7590-VHVEG  Female              0     Yes         No  No phone service   \n",
       "5575-GNVDE    Male              0      No         No                No   \n",
       "3668-QPYBK    Male              0      No         No                No   \n",
       "7795-CFOCW    Male              0      No         No  No phone service   \n",
       "9237-HQITU  Female              0      No         No                No   \n",
       "...            ...            ...     ...        ...               ...   \n",
       "2569-WGERO  Female              0      No         No                No   \n",
       "6840-RESVB    Male              0     Yes        Yes               Yes   \n",
       "2234-XADUH  Female              0     Yes        Yes               Yes   \n",
       "4801-JZAZL  Female              0     Yes        Yes  No phone service   \n",
       "8361-LTMKD    Male              1     Yes         No               Yes   \n",
       "\n",
       "           InternetService       OnlineSecurity         OnlineBackup  \\\n",
       "customerID                                                             \n",
       "7590-VHVEG             DSL                   No                  Yes   \n",
       "5575-GNVDE             DSL                  Yes                   No   \n",
       "3668-QPYBK             DSL                  Yes                  Yes   \n",
       "7795-CFOCW             DSL                  Yes                   No   \n",
       "9237-HQITU     Fiber optic                   No                   No   \n",
       "...                    ...                  ...                  ...   \n",
       "2569-WGERO              No  No internet service  No internet service   \n",
       "6840-RESVB             DSL                  Yes                   No   \n",
       "2234-XADUH     Fiber optic                   No                  Yes   \n",
       "4801-JZAZL             DSL                  Yes                   No   \n",
       "8361-LTMKD     Fiber optic                   No                   No   \n",
       "\n",
       "               DeviceProtection          TechSupport  ...  \\\n",
       "customerID                                            ...   \n",
       "7590-VHVEG                   No                   No  ...   \n",
       "5575-GNVDE                  Yes                   No  ...   \n",
       "3668-QPYBK                   No                   No  ...   \n",
       "7795-CFOCW                  Yes                  Yes  ...   \n",
       "9237-HQITU                   No                   No  ...   \n",
       "...                         ...                  ...  ...   \n",
       "2569-WGERO  No internet service  No internet service  ...   \n",
       "6840-RESVB                  Yes                  Yes  ...   \n",
       "2234-XADUH                  Yes                   No  ...   \n",
       "4801-JZAZL                   No                   No  ...   \n",
       "8361-LTMKD                   No                   No  ...   \n",
       "\n",
       "                StreamingMovies Unnamed: 13  tenure  PhoneService  \\\n",
       "customerID                                                          \n",
       "7590-VHVEG                   No         NaN       1            No   \n",
       "5575-GNVDE                   No         NaN      34           Yes   \n",
       "3668-QPYBK                   No         NaN       2           Yes   \n",
       "7795-CFOCW                   No         NaN      45            No   \n",
       "9237-HQITU                   No         NaN       2           Yes   \n",
       "...                         ...         ...     ...           ...   \n",
       "2569-WGERO  No internet service         NaN      72           Yes   \n",
       "6840-RESVB                  Yes         NaN      24           Yes   \n",
       "2234-XADUH                  Yes         NaN      72           Yes   \n",
       "4801-JZAZL                   No         NaN      11            No   \n",
       "8361-LTMKD                   No         NaN       4           Yes   \n",
       "\n",
       "                  Contract PaperlessBilling              PaymentMethod  \\\n",
       "customerID                                                               \n",
       "7590-VHVEG  Month-to-month              Yes           Electronic check   \n",
       "5575-GNVDE        One year               No               Mailed check   \n",
       "3668-QPYBK  Month-to-month              Yes               Mailed check   \n",
       "7795-CFOCW        One year               No  Bank transfer (automatic)   \n",
       "9237-HQITU  Month-to-month              Yes           Electronic check   \n",
       "...                    ...              ...                        ...   \n",
       "2569-WGERO        Two year              Yes  Bank transfer (automatic)   \n",
       "6840-RESVB        One year              Yes               Mailed check   \n",
       "2234-XADUH        One year              Yes    Credit card (automatic)   \n",
       "4801-JZAZL  Month-to-month              Yes           Electronic check   \n",
       "8361-LTMKD  Month-to-month              Yes               Mailed check   \n",
       "\n",
       "           MonthlyCharges  TotalCharges Churn  \n",
       "customerID                                     \n",
       "7590-VHVEG          29.85         29.85    No  \n",
       "5575-GNVDE          56.95        1889.5    No  \n",
       "3668-QPYBK          53.85        108.15   Yes  \n",
       "7795-CFOCW          42.30       1840.75    No  \n",
       "9237-HQITU          70.70        151.65   Yes  \n",
       "...                   ...           ...   ...  \n",
       "2569-WGERO          21.15        1419.4    No  \n",
       "6840-RESVB          84.80        1990.5    No  \n",
       "2234-XADUH         103.20        7362.9    No  \n",
       "4801-JZAZL          29.60        346.45    No  \n",
       "8361-LTMKD          74.40         306.6   Yes  \n",
       "\n",
       "[7042 rows x 21 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"churn_data.csv\", index_col='customerID', keep_default_na=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "every-preliminary",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 7042 entries, 7590-VHVEG to 8361-LTMKD\n",
      "Data columns (total 21 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   gender            7042 non-null   object \n",
      " 1   SeniorCitizen     7042 non-null   int64  \n",
      " 2   Partner           7042 non-null   object \n",
      " 3   Dependents        7042 non-null   object \n",
      " 4   MultipleLines     7042 non-null   object \n",
      " 5   InternetService   7042 non-null   object \n",
      " 6   OnlineSecurity    7042 non-null   object \n",
      " 7   OnlineBackup      7042 non-null   object \n",
      " 8   DeviceProtection  7042 non-null   object \n",
      " 9   TechSupport       7042 non-null   object \n",
      " 10  StreamingTV       7042 non-null   object \n",
      " 11  StreamingMovies   7042 non-null   object \n",
      " 12  Unnamed: 13       0 non-null      float64\n",
      " 13  tenure            7042 non-null   int64  \n",
      " 14  PhoneService      7042 non-null   object \n",
      " 15  Contract          7042 non-null   object \n",
      " 16  PaperlessBilling  7042 non-null   object \n",
      " 17  PaymentMethod     7042 non-null   object \n",
      " 18  MonthlyCharges    7042 non-null   float64\n",
      " 19  TotalCharges      7042 non-null   object \n",
      " 20  Churn             7042 non-null   object \n",
      "dtypes: float64(2), int64(2), object(17)\n",
      "memory usage: 1.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "prepared-discovery",
   "metadata": {},
   "source": [
    "### Unnamed: 13 has no non-null values, so it is useless col and must be removed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "compressed-rubber",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop('Unnamed: 13', axis=1, inplace=True)\n",
    "# As we can see here some objects need the convertion into float\n",
    "df[\"TotalCharges\"] = df[\"TotalCharges\"].str.replace(' ', '0', regex=True).astype('float')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "particular-newman",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['gender', 'Partner', 'Dependents', 'MultipleLines', 'InternetService',\n",
       "       'OnlineSecurity', 'OnlineBackup', 'DeviceProtection', 'TechSupport',\n",
       "       'StreamingTV', 'StreamingMovies', 'PhoneService', 'Contract',\n",
       "       'PaperlessBilling', 'PaymentMethod', 'Churn'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Obj columns for encoding\n",
    "obj_cols = df.columns[df.dtypes == 'O']\n",
    "obj_cols   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "unlimited-sheet",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gender :  ['Female' 'Male']\n",
      "Partner :  ['Yes' 'No']\n",
      "Dependents :  ['No' 'Yes']\n",
      "MultipleLines :  ['No phone service' 'No' 'Yes']\n",
      "InternetService :  ['DSL' 'Fiber optic' 'No']\n",
      "OnlineSecurity :  ['No' 'Yes' 'No internet service']\n",
      "OnlineBackup :  ['Yes' 'No' 'No internet service']\n",
      "DeviceProtection :  ['No' 'Yes' 'No internet service']\n",
      "TechSupport :  ['No' 'Yes' 'No internet service']\n",
      "StreamingTV :  ['No' 'Yes' 'No internet service']\n",
      "StreamingMovies :  ['No' 'Yes' 'No internet service']\n",
      "PhoneService :  ['No' 'Yes']\n",
      "Contract :  ['Month-to-month' 'One year' 'Two year']\n",
      "PaperlessBilling :  ['Yes' 'No']\n",
      "PaymentMethod :  ['Electronic check' 'Mailed check' 'Bank transfer (automatic)'\n",
      " 'Credit card (automatic)']\n",
      "Churn :  ['No' 'Yes']\n"
     ]
    }
   ],
   "source": [
    "#look at the types of unique values in columns\n",
    "for x in df:\n",
    "    if df[x].dtype =='O':\n",
    "        print(x, \": \",df[x].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "hollywood-lotus",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>customerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7590-VHVEG</th>\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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5575-GNVDE</th>\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>34</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3668-QPYBK</th>\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>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7795-CFOCW</th>\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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9237-HQITU</th>\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>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2569-WGERO</th>\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>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>21.15</td>\n",
       "      <td>1419.40</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6840-RESVB</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2234-XADUH</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.90</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4801-JZAZL</th>\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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8361-LTMKD</th>\n",
       "      <td>1</td>\n",
       "      <td>1</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.60</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7042 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            gender  SeniorCitizen  Partner  Dependents  MultipleLines  \\\n",
       "customerID                                                              \n",
       "7590-VHVEG       0              0        1           0             -1   \n",
       "5575-GNVDE       1              0        0           0              0   \n",
       "3668-QPYBK       1              0        0           0              0   \n",
       "7795-CFOCW       1              0        0           0             -1   \n",
       "9237-HQITU       0              0        0           0              0   \n",
       "...            ...            ...      ...         ...            ...   \n",
       "2569-WGERO       0              0        0           0              0   \n",
       "6840-RESVB       1              0        1           1              1   \n",
       "2234-XADUH       0              0        1           1              1   \n",
       "4801-JZAZL       0              0        1           1             -1   \n",
       "8361-LTMKD       1              1        1           0              1   \n",
       "\n",
       "            InternetService  OnlineSecurity  OnlineBackup  DeviceProtection  \\\n",
       "customerID                                                                    \n",
       "7590-VHVEG                0               0             1                 0   \n",
       "5575-GNVDE                0               1             0                 1   \n",
       "3668-QPYBK                0               1             1                 0   \n",
       "7795-CFOCW                0               1             0                 1   \n",
       "9237-HQITU                1               0             0                 0   \n",
       "...                     ...             ...           ...               ...   \n",
       "2569-WGERO               -1              -1            -1                -1   \n",
       "6840-RESVB                0               1             0                 1   \n",
       "2234-XADUH                1               0             1                 1   \n",
       "4801-JZAZL                0               1             0                 0   \n",
       "8361-LTMKD                1               0             0                 0   \n",
       "\n",
       "            TechSupport  StreamingTV  StreamingMovies  tenure  PhoneService  \\\n",
       "customerID                                                                    \n",
       "7590-VHVEG            0            0                0       1             0   \n",
       "5575-GNVDE            0            0                0      34             1   \n",
       "3668-QPYBK            0            0                0       2             1   \n",
       "7795-CFOCW            1            0                0      45             0   \n",
       "9237-HQITU            0            0                0       2             1   \n",
       "...                 ...          ...              ...     ...           ...   \n",
       "2569-WGERO           -1           -1               -1      72             1   \n",
       "6840-RESVB            1            1                1      24             1   \n",
       "2234-XADUH            0            1                1      72             1   \n",
       "4801-JZAZL            0            0                0      11             0   \n",
       "8361-LTMKD            0            0                0       4             1   \n",
       "\n",
       "            Contract  PaperlessBilling  PaymentMethod  MonthlyCharges  \\\n",
       "customerID                                                              \n",
       "7590-VHVEG         0                 1              0           29.85   \n",
       "5575-GNVDE         1                 0              1           56.95   \n",
       "3668-QPYBK         0                 1              1           53.85   \n",
       "7795-CFOCW         1                 0              2           42.30   \n",
       "9237-HQITU         0                 1              0           70.70   \n",
       "...              ...               ...            ...             ...   \n",
       "2569-WGERO         2                 1              2           21.15   \n",
       "6840-RESVB         1                 1              1           84.80   \n",
       "2234-XADUH         1                 1              3          103.20   \n",
       "4801-JZAZL         0                 1              0           29.60   \n",
       "8361-LTMKD         0                 1              1           74.40   \n",
       "\n",
       "            TotalCharges  Churn  \n",
       "customerID                       \n",
       "7590-VHVEG         29.85      0  \n",
       "5575-GNVDE       1889.50      0  \n",
       "3668-QPYBK        108.15      1  \n",
       "7795-CFOCW       1840.75      0  \n",
       "9237-HQITU        151.65      1  \n",
       "...                  ...    ...  \n",
       "2569-WGERO       1419.40      0  \n",
       "6840-RESVB       1990.50      0  \n",
       "2234-XADUH       7362.90      0  \n",
       "4801-JZAZL        346.45      0  \n",
       "8361-LTMKD        306.60      1  \n",
       "\n",
       "[7042 rows x 20 columns]"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# using ordinal encoding\n",
    "dummied = ce.OrdinalEncoder(cols=obj_cols, return_df=True, drop_invariant=False,\n",
    "    handle_unknown=\"value\", handle_missing=\"value\",\n",
    "    mapping=[{'col': 'gender', 'mapping': {'Male':1, 'Female':0}}, # two options and 1 for Male 0 for Female\n",
    "        {'col': 'Partner', 'mapping': {'Yes':1, 'No':0}}, # two options and 1 for 'yes' 0 for 'no'\n",
    "        {'col': 'Dependents', 'mapping': {'Yes':1, 'No':0}}, # two options and 1 for 'yes' 0 for 'no'\n",
    "        {'col': 'MultipleLines', 'mapping': {'No phone service':-1,'Yes':1, 'No':0}}, # two options and 1 for 'yes' 0 for 'no'\n",
    "        {'col': 'InternetService', 'mapping': {'DSL':0,'Fiber optic':1, 'No':-1}}, # here 'no' has the negative value as it is not an option\n",
    "        {'col': 'OnlineSecurity', 'mapping': {'No internet service':-1,'Yes':1, 'No':0}}, # added -1 for default or nonekind of option\n",
    "        {'col': 'OnlineBackup', 'mapping': {'No internet service':-1,'Yes':1, 'No':0}}, # added -1 for default or nonekind of option\n",
    "        {'col': 'DeviceProtection', 'mapping': {'No internet service':-1,'Yes':1, 'No':0}}, # added -1 for default or nonekind of option\n",
    "        {'col': 'TechSupport', 'mapping': {'No internet service':-1,'Yes':1, 'No':0}}, # added -1 for default or nonekind of option\n",
    "        {'col': 'StreamingTV', 'mapping': {'No internet service':-1,'Yes':1, 'No':0}}, # added -1 for default or nonekind of option\n",
    "        {'col': 'StreamingMovies', 'mapping': {'No internet service':-1,'Yes':1, 'No':0}}, # added -1 for default or nonekind of option\n",
    "        {'col': 'PhoneService', 'mapping': {'Yes':1, 'No':0}}, # two options and 1 for 'yes' 0 for 'no'\n",
    "        {'col': 'Contract', 'mapping': {'Month-to-month':0,'One year':1, 'Two year':2}}, #here we put 0,1,2 since all of them are options\n",
    "        {'col': 'PaperlessBilling', 'mapping': {'Yes':1, 'No':0}}, # two options and 1 for 'yes' 0 for 'no'\n",
    "        {'col': 'PaymentMethod', 'mapping': {'Electronic check':0,'Mailed check':1, 'Bank transfer (automatic)':2, 'Credit card (automatic)':3}}, #here we put 0,1,2,3 since all of them are options\n",
    "        {'col': 'Churn', 'mapping': {'Yes':1, 'No':0}},]).fit(df) # fit to dataframe\n",
    "\n",
    "encoded = dummied.transform(df)\n",
    "# fit and transform into dataframe\n",
    "encoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "rising-dylan",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 7042 entries, 7590-VHVEG to 8361-LTMKD\n",
      "Data columns (total 20 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   gender            7042 non-null   int64  \n",
      " 1   SeniorCitizen     7042 non-null   int64  \n",
      " 2   Partner           7042 non-null   int64  \n",
      " 3   Dependents        7042 non-null   int64  \n",
      " 4   MultipleLines     7042 non-null   int64  \n",
      " 5   InternetService   7042 non-null   int64  \n",
      " 6   OnlineSecurity    7042 non-null   int64  \n",
      " 7   OnlineBackup      7042 non-null   int64  \n",
      " 8   DeviceProtection  7042 non-null   int64  \n",
      " 9   TechSupport       7042 non-null   int64  \n",
      " 10  StreamingTV       7042 non-null   int64  \n",
      " 11  StreamingMovies   7042 non-null   int64  \n",
      " 12  tenure            7042 non-null   int64  \n",
      " 13  PhoneService      7042 non-null   int64  \n",
      " 14  Contract          7042 non-null   int64  \n",
      " 15  PaperlessBilling  7042 non-null   int64  \n",
      " 16  PaymentMethod     7042 non-null   int64  \n",
      " 17  MonthlyCharges    7042 non-null   float64\n",
      " 18  TotalCharges      7042 non-null   float64\n",
      " 19  Churn             7042 non-null   int64  \n",
      "dtypes: float64(2), int64(18)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "encoded.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "linear-special",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bias</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>customerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7590-VHVEG</th>\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>...</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>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5575-GNVDE</th>\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>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3668-QPYBK</th>\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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7795-CFOCW</th>\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>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9237-HQITU</th>\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>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2569-WGERO</th>\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>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>...</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>21.15</td>\n",
       "      <td>1419.40</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6840-RESVB</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>84.80</td>\n",
       "      <td>1990.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2234-XADUH</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>103.20</td>\n",
       "      <td>7362.90</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4801-JZAZL</th>\n",
       "      <td>1</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>29.60</td>\n",
       "      <td>346.45</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8361-LTMKD</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>74.40</td>\n",
       "      <td>306.60</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7042 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            bias  gender  SeniorCitizen  Partner  Dependents  MultipleLines  \\\n",
       "customerID                                                                    \n",
       "7590-VHVEG     1       0              0        1           0             -1   \n",
       "5575-GNVDE     1       1              0        0           0              0   \n",
       "3668-QPYBK     1       1              0        0           0              0   \n",
       "7795-CFOCW     1       1              0        0           0             -1   \n",
       "9237-HQITU     1       0              0        0           0              0   \n",
       "...          ...     ...            ...      ...         ...            ...   \n",
       "2569-WGERO     1       0              0        0           0              0   \n",
       "6840-RESVB     1       1              0        1           1              1   \n",
       "2234-XADUH     1       0              0        1           1              1   \n",
       "4801-JZAZL     1       0              0        1           1             -1   \n",
       "8361-LTMKD     1       1              1        1           0              1   \n",
       "\n",
       "            InternetService  OnlineSecurity  OnlineBackup  DeviceProtection  \\\n",
       "customerID                                                                    \n",
       "7590-VHVEG                0               0             1                 0   \n",
       "5575-GNVDE                0               1             0                 1   \n",
       "3668-QPYBK                0               1             1                 0   \n",
       "7795-CFOCW                0               1             0                 1   \n",
       "9237-HQITU                1               0             0                 0   \n",
       "...                     ...             ...           ...               ...   \n",
       "2569-WGERO               -1              -1            -1                -1   \n",
       "6840-RESVB                0               1             0                 1   \n",
       "2234-XADUH                1               0             1                 1   \n",
       "4801-JZAZL                0               1             0                 0   \n",
       "8361-LTMKD                1               0             0                 0   \n",
       "\n",
       "            ...  StreamingTV  StreamingMovies  tenure  PhoneService  Contract  \\\n",
       "customerID  ...                                                                 \n",
       "7590-VHVEG  ...            0                0       1             0         0   \n",
       "5575-GNVDE  ...            0                0      34             1         1   \n",
       "3668-QPYBK  ...            0                0       2             1         0   \n",
       "7795-CFOCW  ...            0                0      45             0         1   \n",
       "9237-HQITU  ...            0                0       2             1         0   \n",
       "...         ...          ...              ...     ...           ...       ...   \n",
       "2569-WGERO  ...           -1               -1      72             1         2   \n",
       "6840-RESVB  ...            1                1      24             1         1   \n",
       "2234-XADUH  ...            1                1      72             1         1   \n",
       "4801-JZAZL  ...            0                0      11             0         0   \n",
       "8361-LTMKD  ...            0                0       4             1         0   \n",
       "\n",
       "            PaperlessBilling  PaymentMethod  MonthlyCharges  TotalCharges  \\\n",
       "customerID                                                                  \n",
       "7590-VHVEG                 1              0           29.85         29.85   \n",
       "5575-GNVDE                 0              1           56.95       1889.50   \n",
       "3668-QPYBK                 1              1           53.85        108.15   \n",
       "7795-CFOCW                 0              2           42.30       1840.75   \n",
       "9237-HQITU                 1              0           70.70        151.65   \n",
       "...                      ...            ...             ...           ...   \n",
       "2569-WGERO                 1              2           21.15       1419.40   \n",
       "6840-RESVB                 1              1           84.80       1990.50   \n",
       "2234-XADUH                 1              3          103.20       7362.90   \n",
       "4801-JZAZL                 1              0           29.60        346.45   \n",
       "8361-LTMKD                 1              1           74.40        306.60   \n",
       "\n",
       "            Churn  \n",
       "customerID         \n",
       "7590-VHVEG      0  \n",
       "5575-GNVDE      0  \n",
       "3668-QPYBK      1  \n",
       "7795-CFOCW      0  \n",
       "9237-HQITU      1  \n",
       "...           ...  \n",
       "2569-WGERO      0  \n",
       "6840-RESVB      0  \n",
       "2234-XADUH      0  \n",
       "4801-JZAZL      0  \n",
       "8361-LTMKD      1  \n",
       "\n",
       "[7042 rows x 21 columns]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# adding bias column\n",
    "encoded.insert(0, \"bias\", 1)\n",
    "encoded"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "increasing-diameter",
   "metadata": {},
   "source": [
    "### Oversampling (optional as it did not help at all)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "acoustic-lucas",
   "metadata": {},
   "outputs": [],
   "source": [
    "#minor_class = encoded[encoded[\"Churn\"] == 1].sample(frac=1)   # to shuffle df\n",
    "#minor_class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "loose-editor",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.734592\n",
       "1    0.265408\n",
       "Name: Churn, dtype: float64"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "encoded[\"Churn\"].value_counts(normalize=True)   # class 1 is under-represented"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "front-pioneer",
   "metadata": {},
   "outputs": [],
   "source": [
    "#encoded = encoded.append(minor_class).sample(frac=1)   # to shuffle df\n",
    "#encoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "spread-novel",
   "metadata": {},
   "outputs": [],
   "source": [
    "#encoded[\"Churn\"].value_counts(normalize=True) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "legislative-millennium",
   "metadata": {},
   "source": [
    "### Train/test split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "completed-occurrence",
   "metadata": {},
   "outputs": [],
   "source": [
    "# split into train/test\n",
    "def split(data, train_frac, test_frac, validation_frac=0):\n",
    "    rows = data.shape[0]\n",
    "    if validation_frac:\n",
    "        return (data.iloc[:int(rows*train_frac), :],\n",
    "                data.iloc[int(rows*train_frac):int(rows*test_frac), :],\n",
    "                data.iloc[int(rows*test_frac):int(rows*validation_frac), :])\n",
    "    else:\n",
    "        return (data.iloc[:int(rows*train_frac), :],\n",
    "                data.iloc[int(rows*train_frac):, :])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "laden-yugoslavia",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5633, 21)\n",
      "(1409, 21)\n",
      "7042\n"
     ]
    }
   ],
   "source": [
    "train, test = split(encoded, 0.8, 0.2, 0)\n",
    "print(train.shape)\n",
    "print(test.shape)\n",
    "print(train.shape[0]+test.shape[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "hairy-rebel",
   "metadata": {},
   "source": [
    "### Pay attention to the ration for example gender column : ration is sustainable accross whole dataset / train/test/valid and equal to 50%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "statutory-plaza",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bias</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7042.0</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "      <td>7042.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.504686</td>\n",
       "      <td>0.162170</td>\n",
       "      <td>0.483101</td>\n",
       "      <td>0.299631</td>\n",
       "      <td>0.325050</td>\n",
       "      <td>0.222806</td>\n",
       "      <td>0.069867</td>\n",
       "      <td>0.128231</td>\n",
       "      <td>0.127095</td>\n",
       "      <td>...</td>\n",
       "      <td>0.167566</td>\n",
       "      <td>0.171116</td>\n",
       "      <td>32.366373</td>\n",
       "      <td>0.903153</td>\n",
       "      <td>0.690287</td>\n",
       "      <td>0.592161</td>\n",
       "      <td>1.315535</td>\n",
       "      <td>64.755886</td>\n",
       "      <td>2279.086083</td>\n",
       "      <td>0.265408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.500014</td>\n",
       "      <td>0.368633</td>\n",
       "      <td>0.499750</td>\n",
       "      <td>0.458129</td>\n",
       "      <td>0.642764</td>\n",
       "      <td>0.778877</td>\n",
       "      <td>0.706014</td>\n",
       "      <td>0.738420</td>\n",
       "      <td>0.737847</td>\n",
       "      <td>...</td>\n",
       "      <td>0.756947</td>\n",
       "      <td>0.758496</td>\n",
       "      <td>24.557955</td>\n",
       "      <td>0.295771</td>\n",
       "      <td>0.833668</td>\n",
       "      <td>0.491468</td>\n",
       "      <td>1.148960</td>\n",
       "      <td>30.088238</td>\n",
       "      <td>2266.302524</td>\n",
       "      <td>0.441581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>35.500000</td>\n",
       "      <td>398.550000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>70.350000</td>\n",
       "      <td>1394.075000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>89.850000</td>\n",
       "      <td>3783.600000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>118.750000</td>\n",
       "      <td>8684.800000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         bias       gender  SeniorCitizen      Partner   Dependents  \\\n",
       "count  7042.0  7042.000000    7042.000000  7042.000000  7042.000000   \n",
       "mean      1.0     0.504686       0.162170     0.483101     0.299631   \n",
       "std       0.0     0.500014       0.368633     0.499750     0.458129   \n",
       "min       1.0     0.000000       0.000000     0.000000     0.000000   \n",
       "25%       1.0     0.000000       0.000000     0.000000     0.000000   \n",
       "50%       1.0     1.000000       0.000000     0.000000     0.000000   \n",
       "75%       1.0     1.000000       0.000000     1.000000     1.000000   \n",
       "max       1.0     1.000000       1.000000     1.000000     1.000000   \n",
       "\n",
       "       MultipleLines  InternetService  OnlineSecurity  OnlineBackup  \\\n",
       "count    7042.000000      7042.000000     7042.000000   7042.000000   \n",
       "mean        0.325050         0.222806        0.069867      0.128231   \n",
       "std         0.642764         0.778877        0.706014      0.738420   \n",
       "min        -1.000000        -1.000000       -1.000000     -1.000000   \n",
       "25%         0.000000         0.000000        0.000000      0.000000   \n",
       "50%         0.000000         0.000000        0.000000      0.000000   \n",
       "75%         1.000000         1.000000        1.000000      1.000000   \n",
       "max         1.000000         1.000000        1.000000      1.000000   \n",
       "\n",
       "       DeviceProtection  ...  StreamingTV  StreamingMovies       tenure  \\\n",
       "count       7042.000000  ...  7042.000000      7042.000000  7042.000000   \n",
       "mean           0.127095  ...     0.167566         0.171116    32.366373   \n",
       "std            0.737847  ...     0.756947         0.758496    24.557955   \n",
       "min           -1.000000  ...    -1.000000        -1.000000     0.000000   \n",
       "25%            0.000000  ...     0.000000         0.000000     9.000000   \n",
       "50%            0.000000  ...     0.000000         0.000000    29.000000   \n",
       "75%            1.000000  ...     1.000000         1.000000    55.000000   \n",
       "max            1.000000  ...     1.000000         1.000000    72.000000   \n",
       "\n",
       "       PhoneService     Contract  PaperlessBilling  PaymentMethod  \\\n",
       "count   7042.000000  7042.000000       7042.000000    7042.000000   \n",
       "mean       0.903153     0.690287          0.592161       1.315535   \n",
       "std        0.295771     0.833668          0.491468       1.148960   \n",
       "min        0.000000     0.000000          0.000000       0.000000   \n",
       "25%        1.000000     0.000000          0.000000       0.000000   \n",
       "50%        1.000000     0.000000          1.000000       1.000000   \n",
       "75%        1.000000     1.000000          1.000000       2.000000   \n",
       "max        1.000000     2.000000          1.000000       3.000000   \n",
       "\n",
       "       MonthlyCharges  TotalCharges        Churn  \n",
       "count     7042.000000   7042.000000  7042.000000  \n",
       "mean        64.755886   2279.086083     0.265408  \n",
       "std         30.088238   2266.302524     0.441581  \n",
       "min         18.250000      0.000000     0.000000  \n",
       "25%         35.500000    398.550000     0.000000  \n",
       "50%         70.350000   1394.075000     0.000000  \n",
       "75%         89.850000   3783.600000     1.000000  \n",
       "max        118.750000   8684.800000     1.000000  \n",
       "\n",
       "[8 rows x 21 columns]"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "encoded.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "seven-entertainment",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bias</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5633.0</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "      <td>5633.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.504527</td>\n",
       "      <td>0.160483</td>\n",
       "      <td>0.482514</td>\n",
       "      <td>0.297177</td>\n",
       "      <td>0.332150</td>\n",
       "      <td>0.222794</td>\n",
       "      <td>0.070833</td>\n",
       "      <td>0.126931</td>\n",
       "      <td>0.128173</td>\n",
       "      <td>...</td>\n",
       "      <td>0.167939</td>\n",
       "      <td>0.170247</td>\n",
       "      <td>32.301260</td>\n",
       "      <td>0.907509</td>\n",
       "      <td>0.685780</td>\n",
       "      <td>0.591869</td>\n",
       "      <td>1.320966</td>\n",
       "      <td>64.874321</td>\n",
       "      <td>2278.602592</td>\n",
       "      <td>0.264158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.500024</td>\n",
       "      <td>0.367086</td>\n",
       "      <td>0.499738</td>\n",
       "      <td>0.457056</td>\n",
       "      <td>0.637871</td>\n",
       "      <td>0.779645</td>\n",
       "      <td>0.707450</td>\n",
       "      <td>0.738578</td>\n",
       "      <td>0.739205</td>\n",
       "      <td>...</td>\n",
       "      <td>0.757905</td>\n",
       "      <td>0.758912</td>\n",
       "      <td>24.588285</td>\n",
       "      <td>0.289743</td>\n",
       "      <td>0.832557</td>\n",
       "      <td>0.491531</td>\n",
       "      <td>1.148561</td>\n",
       "      <td>30.097896</td>\n",
       "      <td>2268.438761</td>\n",
       "      <td>0.440923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>35.650000</td>\n",
       "      <td>390.400000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>70.450000</td>\n",
       "      <td>1398.250000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>89.900000</td>\n",
       "      <td>3770.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>118.750000</td>\n",
       "      <td>8684.800000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         bias       gender  SeniorCitizen      Partner   Dependents  \\\n",
       "count  5633.0  5633.000000    5633.000000  5633.000000  5633.000000   \n",
       "mean      1.0     0.504527       0.160483     0.482514     0.297177   \n",
       "std       0.0     0.500024       0.367086     0.499738     0.457056   \n",
       "min       1.0     0.000000       0.000000     0.000000     0.000000   \n",
       "25%       1.0     0.000000       0.000000     0.000000     0.000000   \n",
       "50%       1.0     1.000000       0.000000     0.000000     0.000000   \n",
       "75%       1.0     1.000000       0.000000     1.000000     1.000000   \n",
       "max       1.0     1.000000       1.000000     1.000000     1.000000   \n",
       "\n",
       "       MultipleLines  InternetService  OnlineSecurity  OnlineBackup  \\\n",
       "count    5633.000000      5633.000000     5633.000000   5633.000000   \n",
       "mean        0.332150         0.222794        0.070833      0.126931   \n",
       "std         0.637871         0.779645        0.707450      0.738578   \n",
       "min        -1.000000        -1.000000       -1.000000     -1.000000   \n",
       "25%         0.000000         0.000000        0.000000      0.000000   \n",
       "50%         0.000000         0.000000        0.000000      0.000000   \n",
       "75%         1.000000         1.000000        1.000000      1.000000   \n",
       "max         1.000000         1.000000        1.000000      1.000000   \n",
       "\n",
       "       DeviceProtection  ...  StreamingTV  StreamingMovies       tenure  \\\n",
       "count       5633.000000  ...  5633.000000      5633.000000  5633.000000   \n",
       "mean           0.128173  ...     0.167939         0.170247    32.301260   \n",
       "std            0.739205  ...     0.757905         0.758912    24.588285   \n",
       "min           -1.000000  ...    -1.000000        -1.000000     0.000000   \n",
       "25%            0.000000  ...     0.000000         0.000000     9.000000   \n",
       "50%            0.000000  ...     0.000000         0.000000    29.000000   \n",
       "75%            1.000000  ...     1.000000         1.000000    55.000000   \n",
       "max            1.000000  ...     1.000000         1.000000    72.000000   \n",
       "\n",
       "       PhoneService     Contract  PaperlessBilling  PaymentMethod  \\\n",
       "count   5633.000000  5633.000000       5633.000000    5633.000000   \n",
       "mean       0.907509     0.685780          0.591869       1.320966   \n",
       "std        0.289743     0.832557          0.491531       1.148561   \n",
       "min        0.000000     0.000000          0.000000       0.000000   \n",
       "25%        1.000000     0.000000          0.000000       0.000000   \n",
       "50%        1.000000     0.000000          1.000000       1.000000   \n",
       "75%        1.000000     1.000000          1.000000       2.000000   \n",
       "max        1.000000     2.000000          1.000000       3.000000   \n",
       "\n",
       "       MonthlyCharges  TotalCharges        Churn  \n",
       "count     5633.000000   5633.000000  5633.000000  \n",
       "mean        64.874321   2278.602592     0.264158  \n",
       "std         30.097896   2268.438761     0.440923  \n",
       "min         18.250000      0.000000     0.000000  \n",
       "25%         35.650000    390.400000     0.000000  \n",
       "50%         70.450000   1398.250000     0.000000  \n",
       "75%         89.900000   3770.000000     1.000000  \n",
       "max        118.750000   8684.800000     1.000000  \n",
       "\n",
       "[8 rows x 21 columns]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "spoken-envelope",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bias</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>OnlineBackup</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1409.0</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "      <td>1409.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.505323</td>\n",
       "      <td>0.168914</td>\n",
       "      <td>0.485451</td>\n",
       "      <td>0.309439</td>\n",
       "      <td>0.296664</td>\n",
       "      <td>0.222853</td>\n",
       "      <td>0.066004</td>\n",
       "      <td>0.133428</td>\n",
       "      <td>0.122782</td>\n",
       "      <td>...</td>\n",
       "      <td>0.166075</td>\n",
       "      <td>0.174592</td>\n",
       "      <td>32.626686</td>\n",
       "      <td>0.885735</td>\n",
       "      <td>0.708304</td>\n",
       "      <td>0.593329</td>\n",
       "      <td>1.293825</td>\n",
       "      <td>64.282399</td>\n",
       "      <td>2281.019021</td>\n",
       "      <td>0.270405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.500149</td>\n",
       "      <td>0.374809</td>\n",
       "      <td>0.499966</td>\n",
       "      <td>0.462427</td>\n",
       "      <td>0.661435</td>\n",
       "      <td>0.776073</td>\n",
       "      <td>0.700478</td>\n",
       "      <td>0.738027</td>\n",
       "      <td>0.732639</td>\n",
       "      <td>...</td>\n",
       "      <td>0.753372</td>\n",
       "      <td>0.757093</td>\n",
       "      <td>24.443285</td>\n",
       "      <td>0.318246</td>\n",
       "      <td>0.838150</td>\n",
       "      <td>0.491387</td>\n",
       "      <td>1.150703</td>\n",
       "      <td>30.055605</td>\n",
       "      <td>2258.544032</td>\n",
       "      <td>0.444327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.550000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>35.200000</td>\n",
       "      <td>413.650000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>70.100000</td>\n",
       "      <td>1375.600000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>89.600000</td>\n",
       "      <td>3827.900000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>118.200000</td>\n",
       "      <td>8670.100000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         bias       gender  SeniorCitizen      Partner   Dependents  \\\n",
       "count  1409.0  1409.000000    1409.000000  1409.000000  1409.000000   \n",
       "mean      1.0     0.505323       0.168914     0.485451     0.309439   \n",
       "std       0.0     0.500149       0.374809     0.499966     0.462427   \n",
       "min       1.0     0.000000       0.000000     0.000000     0.000000   \n",
       "25%       1.0     0.000000       0.000000     0.000000     0.000000   \n",
       "50%       1.0     1.000000       0.000000     0.000000     0.000000   \n",
       "75%       1.0     1.000000       0.000000     1.000000     1.000000   \n",
       "max       1.0     1.000000       1.000000     1.000000     1.000000   \n",
       "\n",
       "       MultipleLines  InternetService  OnlineSecurity  OnlineBackup  \\\n",
       "count    1409.000000      1409.000000     1409.000000   1409.000000   \n",
       "mean        0.296664         0.222853        0.066004      0.133428   \n",
       "std         0.661435         0.776073        0.700478      0.738027   \n",
       "min        -1.000000        -1.000000       -1.000000     -1.000000   \n",
       "25%         0.000000         0.000000        0.000000      0.000000   \n",
       "50%         0.000000         0.000000        0.000000      0.000000   \n",
       "75%         1.000000         1.000000        1.000000      1.000000   \n",
       "max         1.000000         1.000000        1.000000      1.000000   \n",
       "\n",
       "       DeviceProtection  ...  StreamingTV  StreamingMovies       tenure  \\\n",
       "count       1409.000000  ...  1409.000000      1409.000000  1409.000000   \n",
       "mean           0.122782  ...     0.166075         0.174592    32.626686   \n",
       "std            0.732639  ...     0.753372         0.757093    24.443285   \n",
       "min           -1.000000  ...    -1.000000        -1.000000     0.000000   \n",
       "25%            0.000000  ...     0.000000         0.000000     9.000000   \n",
       "50%            0.000000  ...     0.000000         0.000000    30.000000   \n",
       "75%            1.000000  ...     1.000000         1.000000    56.000000   \n",
       "max            1.000000  ...     1.000000         1.000000    72.000000   \n",
       "\n",
       "       PhoneService     Contract  PaperlessBilling  PaymentMethod  \\\n",
       "count   1409.000000  1409.000000       1409.000000    1409.000000   \n",
       "mean       0.885735     0.708304          0.593329       1.293825   \n",
       "std        0.318246     0.838150          0.491387       1.150703   \n",
       "min        0.000000     0.000000          0.000000       0.000000   \n",
       "25%        1.000000     0.000000          0.000000       0.000000   \n",
       "50%        1.000000     0.000000          1.000000       1.000000   \n",
       "75%        1.000000     1.000000          1.000000       2.000000   \n",
       "max        1.000000     2.000000          1.000000       3.000000   \n",
       "\n",
       "       MonthlyCharges  TotalCharges        Churn  \n",
       "count     1409.000000   1409.000000  1409.000000  \n",
       "mean        64.282399   2281.019021     0.270405  \n",
       "std         30.055605   2258.544032     0.444327  \n",
       "min         18.550000      0.000000     0.000000  \n",
       "25%         35.200000    413.650000     0.000000  \n",
       "50%         70.100000   1375.600000     0.000000  \n",
       "75%         89.600000   3827.900000     1.000000  \n",
       "max        118.200000   8670.100000     1.000000  \n",
       "\n",
       "[8 rows x 21 columns]"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "established-corps",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5633, 20)\n",
      "(5633, 1)\n",
      "(1409, 20)\n",
      "(1409, 1)\n"
     ]
    }
   ],
   "source": [
    "n = encoded.shape[1]\n",
    "x_train = train.iloc[:, :n-1].to_numpy()\n",
    "x_test = test.iloc[:, :n-1].to_numpy()\n",
    "m = x_train.shape[0]\n",
    "y_train = train.iloc[:, n-1].to_numpy().reshape([m, 1])\n",
    "y_test = test.iloc[:, n-1].to_numpy().reshape([x_test.shape[0], 1])\n",
    "print(x_train.shape)\n",
    "print(y_train.shape)\n",
    "print(x_test.shape)\n",
    "print(y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "acting-information",
   "metadata": {},
   "outputs": [],
   "source": [
    "def sigmoid(z):\n",
    "    return 1/(1+np.exp(-z))\n",
    "\n",
    "def h(W, X):\n",
    "    return sigmoid(X.dot(W.T))\n",
    "\n",
    "def cost(W, X, Y):\n",
    "    return -np.sum( Y*np.log1p(h(W, X)) + (1-Y)*np.log1p(1-h(W, X)) )/X.shape[0]\n",
    "\n",
    "def confusion_matrix(y_true, y_pred):\n",
    "    true_pos = 0\n",
    "    false_pos = 0\n",
    "    false_neg = 0\n",
    "    true_neg = 0\n",
    "    for index in range(0, y_true.shape[0]):\n",
    "        if y_pred[index][0]:\n",
    "            if y_true[index][0]:\n",
    "                true_pos = true_pos + 1\n",
    "            else:\n",
    "                false_pos = false_pos + 1\n",
    "        else:\n",
    "            if y_true[index][0]:\n",
    "                false_neg = false_neg + 1\n",
    "            else:\n",
    "                true_neg = true_neg + 1\n",
    "            \n",
    "    precision = true_pos/(true_pos+false_pos)\n",
    "    recall = true_pos/(true_pos+false_neg)\n",
    "    return precision, recall, true_pos, true_neg, false_pos, false_neg\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "removed-pierce",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-120-99ee879eee37>:2: RuntimeWarning: overflow encountered in exp\n",
      "  return 1/(1+np.exp(-z))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0: train cost = -0.5090570492134571; train accuracy = 73.4244629859755\n",
      "            Test cost = -0.5090570492134571; test accuracy = 72.81760113555713\n",
      "            Train : precision=0.37540156034878386; recall=0.5497311827956989; f1 = 0.44614125988546494\n",
      "\n",
      "Epoch 2: train cost = -0.509086655998351; train accuracy = 73.4244629859755\n",
      "            Test cost = -0.509086655998351; test accuracy = 72.81760113555713\n",
      "            Train : precision=0.37562301767104667; recall=0.5571236559139785; f1 = 0.4487144790257104\n",
      "\n",
      "Epoch 4: train cost = -0.5091081552890117; train accuracy = 73.4244629859755\n",
      "            Test cost = -0.5091081552890117; test accuracy = 72.81760113555713\n",
      "            Train : precision=0.3740526081141329; recall=0.5638440860215054; f1 = 0.44974537657464486\n",
      "\n",
      "Epoch 6: train cost = -0.5091326425381716; train accuracy = 73.44221551571098\n",
      "            Test cost = -0.5091326425381716; test accuracy = 72.88857345635202\n",
      "            Train : precision=0.3706631532718489; recall=0.5672043010752689; f1 = 0.44833997343957505\n",
      "\n",
      "Epoch 8: train cost = -0.5092581349419755; train accuracy = 73.40671045624002\n",
      "            Test cost = -0.5092581349419755; test accuracy = 73.03051809794181\n",
      "            Train : precision=0.3690579083837511; recall=0.5739247311827957; f1 = 0.4492372435560231\n",
      "\n",
      "Epoch 10: train cost = -0.5099139786242521; train accuracy = 73.21143262914966\n",
      "            Test cost = -0.5099139786242521; test accuracy = 72.60468417317246\n",
      "            Train : precision=0.36862244897959184; recall=0.5826612903225806; f1 = 0.4515625\n",
      "\n",
      "Epoch 12: train cost = -0.51248061605573; train accuracy = 73.05165986153027\n",
      "            Test cost = -0.51248061605573; test accuracy = 72.53371185237758\n",
      "            Train : precision=0.3662911973299958; recall=0.5900537634408602; f1 = 0.451994851994852\n",
      "\n",
      "Epoch 14: train cost = -0.518181613360759; train accuracy = 73.67299840227233\n",
      "            Test cost = -0.518181613360759; test accuracy = 73.88218594748048\n",
      "            Train : precision=0.36531365313653136; recall=0.5987903225806451; f1 = 0.45378151260504196\n",
      "\n",
      "Epoch 16: train cost = -0.5223873657244757; train accuracy = 75.0932007811113\n",
      "            Test cost = -0.5223873657244757; test accuracy = 76.29524485450675\n",
      "            Train : precision=0.3635265700483092; recall=0.6068548387096774; f1 = 0.45468277945619334\n",
      "\n",
      "Epoch 18: train cost = -0.5227918573357344; train accuracy = 75.14645837031777\n",
      "            Test cost = -0.5227918573357344; test accuracy = 76.36621717530163\n",
      "            Train : precision=0.36148382004735596; recall=0.6155913978494624; f1 = 0.45549477871705624\n",
      "\n",
      "Epoch 19: train cost = -0.5225218187928214; train accuracy = 75.14645837031777\n",
      "            Test cost = -0.5225218187928214; test accuracy = 76.36621717530163\n",
      "            Train : precision=0.3612197028928851; recall=0.6209677419354839; f1 = 0.45674740484429066\n",
      "\n"
     ]
    },
    {
     "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": [
    "epochs = 20\n",
    "alpha = 5*10**(-9)\n",
    "#lambd = 10**(3)\n",
    "np.random.seed(2)\n",
    "W = 2*np.random.random([1, n-1]) - 1\n",
    "train_error = []\n",
    "test_error = []\n",
    "for epoch in range(0, epochs):\n",
    "    J_train = cost(W, x_train, y_train)\n",
    "    precision,recall,true_pos,true_neg,false_pos,false_neg=confusion_matrix(y_true=y_train, y_pred=h(W, x_train))\n",
    "    train_error.append(J_train)\n",
    "    J_test = cost(W, x_test, y_test)\n",
    "    test_error.append(J_test)\n",
    "    if epoch%2 == 0 or epoch == epochs-1:\n",
    "        pred = h(W, x_train) >= 0.5\n",
    "        pred = pred + 0\n",
    "        train_accuracy = 100*np.sum(y_train == pred)/m\n",
    "        print(f\"Epoch {epoch}: train cost = {J_train}; train accuracy = {train_accuracy}\")\n",
    "        pred = h(W, x_test) >= 0.5\n",
    "        pred = pred + 0\n",
    "        test_accuracy = 100*np.sum(y_test == pred)/x_test.shape[0]\n",
    "        print(f\"            Test cost = {J_train}; test accuracy = {test_accuracy}\")\n",
    "        print(f\"            Train : precision={precision}; recall={recall};\" + \n",
    "              f\" f1 = {2*precision*recall/(precision+recall)}\\n\")\n",
    "    # update\n",
    "    W = W - alpha*(h(W, x_train) - y_train).T.dot(x_train)   # no reg\n",
    "    #W = (1-alpha*lambd/m)*W - alpha*(h(W, x_train) - y_train).T.dot(x_train)  # l2 regularization\n",
    "    \n",
    "plt.plot(range(0, epochs), train_error, 'r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "understood-friendly",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precision = 0.3606811145510836; recall = 0.6263440860215054; f1 = 0.4577603143418467\n",
      "Tp = 932; Tn = 2493; Fp = 1652; Fn = 556\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-120-99ee879eee37>:2: RuntimeWarning: overflow encountered in exp\n",
      "  return 1/(1+np.exp(-z))\n"
     ]
    }
   ],
   "source": [
    "precision,recall,true_pos,true_neg,false_pos,false_neg = confusion_matrix(y_true=y_train, y_pred=h(W, x_train))\n",
    "print(f\"Precision = {precision}; recall = {recall}; f1 = {2*precision*recall/(precision+recall)}\")\n",
    "print(f\"Tp = {true_pos}; Tn = {true_neg}; Fp = {false_pos}; Fn = {false_neg}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "strategic-digit",
   "metadata": {},
   "source": [
    "### Confusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "pointed-enterprise",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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K6+XOeef/eAQKeUw1L091er7OPamXmpqqLuPnqIy7m9Z/MkAmF2fra4Nz3FPg0TJm4nzFnbugzT9MU93a1SRJfXu0Vsv2g/XeR7PUuX1TuRcroibP11aT52vbHNu3R2sVLeqq/876RocOn5RPpXKSpP/0bqN5/31Hzs43566+3r2VajTopmEjZ6pn1xA99hh/pgEA2ZfP0VEWs1nXU1K0dc8eHVixIre7ZMPZyUkHVqzQuYSELMOE7Nh/+LC2zbefUoF7J/2m+/Lly1nW+Xzs59Yb+JjoDVo6f3mmN8vpn95L0lcLFunM2TgdGr5Pjas3lSSbNqZ9MltxcXFat26dtXzOJNupOBPnjtX3HqsVtTXSpnzYqCHavmWnnqlXS/v3xmrYqCGqVt1XPh5+NkFDQ79GWv9ztHp3fMNavn9vbKajJhbOX2QNU7LjgwEjZblkUeKNaVDvjrt5bIN6dTXxo4l5KlBgUcY86Mq1JF25lpTjej/+fFC7jpzU8E4hMrk468q1JCX/ff1edhV4ZGza8rOeKF/aGiak69S+qf7664q+Xbnptsd7lX1cknTxz5tbvQU842cTJkiSi0sBNW8aoAsXL+nM2YR71HsAwD9NPkfH2+6ekNtyEiZIaSMkctoGcuby5csqW6Gctm/Zqe1bdkqS9m7/OdO6kyZMtn4VKVxYw0YNkZS2pkbjZje3BH22UQPt+mmH/OumjaT++J0Junz5cranY7QIbaaob6IlSV/P/04tQm9OiUnv5/YtO3XmbJxOHD0pn0oV1aNVLy2dv1zVqvsanoKRmX37YnXs+AnFJ1yQq8mk8hW9ra+VLO2p+IQLOT7Hw+SOH305ODjMldRCUlxqamq1O9VH7pqy4keNXrxaUtoUhv4tn1ffFs/dVb01u3+VJBUqUEABb32s7YeOydHRQQ2rPanJfdrL18vTrl0gr0pKTlZBF/tVsAvdmPZj3ntQ3bu0sJZfvnxVl69clcVyRT+ZYzVu8kKVetxdT/neefGo02fO67HH8smtqOu9uwAAAIB7ICk5WZJ0MeFPeZX1UlmvMtbX/vX0U5kekz4KICUlRY6Otp9pF8iwy4ijo6MuJiaqeZtgNW8TrP17Y9Wrw7+1c5tZB85kHlZk5ObupoXzF6lhcD27kQUZ+7l+9xqV8CiuFVuW60L8BW1dv10BlZ/Vu6PeUfM2wdl4F7L29ZqvrFMeUlJSctTWoyA7IxS+kJSzdxX3naODoxr9q7JGd22lb9/vq/++0VFFC7noP9O+0ttzlhmuJ0n/++OsJKn9xzNVuribFg/tpQk9XtYvx39X4ODx+uN83krXgNvxqVhOh478pjNn423K12/aLUk6deqcTfnYyV/K44kWqvCvl/VK9w9UwbuUVi0ZL5dMQomMfj14TN9EbtSLL9RXoUKsUQIAedHrI0Zk+nW/z3nyxqKRr48YIfONXUSAOylYsKB+WBVlfX7seNrWn55lSmnZkq/lWaaUPMuU0rj3J2rr+u23bevWMOGVzh00fWraYpvJScnq0aqXPpjwnt587W35ePipWnVfRSyfIz8/X13PZKR03NlzdmV9/t1bA3sPUZ9/97aWFXBykouLszzLlFLC+QT1addX+R7LJx8PPxVxK6LmbYI1+rOROvP7Wbv2CmSyuGh23Xq9u3aY5ednvzbKo+yOIxRSU1M3Ojg4eN//riAnynkU05rRb9qU9WhSX43f+VQTv12r3s0a6olSJbJdT5L+unJNklT9ibJa+s7NX8ialbz07KBx+nR5tCb0bHufrwx4OPTt2VorVm9Wmy7DNPbDvipV0l2RUVs0Y963kqTLV67a1O/SIVj16z6l+IRErd+0W7/sP2Iz3SEziYl/qW2391TQpYA+Hf2f+3YtAIDcNT8yMtPyacOH39dz9u/c2fo4KCAg00UfgczEJ1xQj1a99Psfp6xbJUpSrbr+atOovXyqVNb3K1dr4tyxhtodNDJM+/b+ok4tX9VvR0/qzNk4za4+U/3e6avtW39S3w5hOvp/R3Ts+Anlz7BTVrqe7fpY13pI91LHFpo+dYZe6nhz5OiYSR8pqFYzNQhsoHVr1mnhygg5Ojrq1R7d1KzOi6pZ21+R30bqp//ZT2GtXeveTR06dvyETdCRF7DaVx6WL5+j3modpI37D2vd3gPWoCC79ZwLpP3SvhL4jE39elUryrukuzbuO3x/LwB4iDR5vramTxqkwe9PU/2mr0uSihYxaer4AeraZ5RcTbZ7ClfwLq0K3qUlSe1aN9LEqYvVtPVb2rv5C1Xx8bZr/8qVa3qx/WAdPX5Kq5dNULkbay4AQGYcHByUmpqa293AXbKYzZKkxj176PCJEzqxJjrbx548fVouBQrYrR+QVblRV5OSFBcfn+XOFrcupnjy9GmbuucSElTAycm6e8TtjsXDITCooQKDbu4IU626r902jFlty5hx28SPPv8g0zpRO1Zmee6CBQtq2bqvrM/TpwiUr+hts0VkuoxlGfuU8XH5it52/U2fQnGrIaMHaMjoAZKkkVPetxtRIEnTFk/ViAGj7RZmvPUcrw/uodcH97jtNIdGjRqxbWRWHBwceknqJUnlSvCH4mHh5eEuSYpPtBiu51ksbTuWx90K29UvWbSw4i7e/tNWIK/p1a2lurQP1i+x/6fr11NU3a+STvx2RpJUqWLZ2x77ystBGvDuZ1qw5Ad99J5tMp2UlKzWnYZq2879+nr+R2pYv8Z9uwYAj65Lly4pIeHmYq0nTqQNO/by8sqtLuEeM/mnffJrMZt18OhR+bdtq08HD1b8xYv6aMYMuZpMKlSooM6cjZN7MTedWBNt3SbSp1JFnY+PV3zCBWtgYdRrw4ZpSVSUynt76djxE4oYM0atg4L02rBhWr15sy5Z0v6fOH34cPUZMUKuJpMuWSwa1a+fJGnYlCnWtlxNJkVOnSp/X1+Z/P2tdX+NjLztNpz4Z8vshj63z53fKb8OHzmsj9+ZYA0f7qadTi1ftQlg8op79h1LTU2dmZqa6p+amupfooh9IoncceRUnCSpRFH7UOBO9fyf9JYk/Z7JWgm/n78gvs/4J3J2LqDaNauqbu1qcnEpoDU/7pAku60ib3X1atqOKhduCeL+/vtvtev2vqLXmxU+fZhaBNe7Px0H8MibPn26vL295e3tLUk2j5E3ZJyrvfiHHyRJ7V94wVpW56mndGTV92khw42V4qO3bpUk7Vr0lQ6tXJWj8y+JitKg7t21b9nXahscrLcnTdT1G5+2XrJYFBIYqIgxY6z1ixd31+oZM9SxRQuNnD5dPpUq6tfISK2eMUOXLBb1HjXSWpcwAY+ysVNHy+/pnE0RatnmxXvUm4cL20bmEQmX/rIru5qUrI+XrNZj+RzVpEZVQ/UkqWWdf8mlQH7NW7NF16/fHLrz/c59+iP+oprk8JcKeNSdPnNen0xaoJrVffT8s2nz6+LOZb5Y6fQbay3Ufvrm71hKSoq69hml777fpGkTB6p9aOP732kAj6zmzZsrPDxc4eFp+7FnfIy84cuxafPPzbGxGjdnjiTZTB0IHz1aktTr5ZetZTOWLJGUNrqheECA9fi7NW7OHJn8/bUkKkpnzsbpu3XrrK8tGj9erYOCrM//O/QdNahZUyWKFdO1pCStnzVb5UqVsm5XeejwEWtd92JuhAl4ZHmWKZXj3R9e7tzqHvXm4ZKdbSMXSQqUVNzBweF3ScNTU1Pn3O+OwZiBs5fqt3MJCqhSUWVKuCnuYqLmr/tJh0/FaWTnlirnUcxQPUkqUcRVH3ZqqUFzlqnxO5+qTf2aOpVwUVO++1HlSxZX2EuNcutygQfuzNl4NWszUC2bN1AZTw+d/P2sZn7xnVJTUzV/5vtycHCQJPUJG6v4hEQ1rF9DZct46OKfFkX/uENrY8wKeMZPHdve3Gt54LCpWrRsrRrWqy4X5wJasPgHm3MGPVdLJT2YQgYgTdWqVVW1aloo2bVrV3Xp0iWXe4R7Lbh+fYV17qz2bw+SJPVp187m9VXbtqlDUJB11IAkPVG2rDY6OSn+xkgFc2xsjhZbTB9FcPDoUXl6eKiwyaSVGzbIvZibXd0SbrZl6f3LTHF397vuE4CHV3Z2eejwIDqCnAmqUVWzozZpVtQmJVj+UsECTqpRoaxGd2ul1vWeNlwv3Vutg1TMtZAmf7dOg+Ysk6uLs9rUr6nR3VrJzbXQg7xEIFeZCrmogrenZkdEKu7cBRV3L6LmTQP0wZDXVKa0h7Veu9DGCl/4veYuWKlz5y+qQIH88qlYTh+PeF39erdR/vw3/+zu+fmQJGnDlr3asGWv3Tl/jJxCoAAgU40aEernVZ1CQjRp/nxJUvtmzWxeGzJurGo88YQm33hdklo+/7ymL16sRItF15KSFNi1q85v3Spng1vdpYcU/ceM0cwPPtAbY0ZrT+yvOrgy6wX1MnI1mTRk3Fhdv3pVv51JW18oJDDQUB8APHrY5SGP6BBYWx0Cbz+H20i9jLoFBahbUMDddg3IE0ymglo2/6M71mvXupHatc7ef/TXr/o8p90C8A+1du3a3O4C7oHqT/qoRJGiNmWVK1SQJI3q189upMEP02eoVViYHnPKr1MxMZKkBjVravrw4XrmlVckSTHh4ZmGCXVqVFdBFxfr41t3W8jn6CiL2axW/frp2W7dVNnb2zrq4aknn9SVqze3Ry7u5mbTniSdjonRwHHjNHHhl3JyLqBTMTHW6Rp1alRXpTK3X7wYwKOJQAEAAADIBeMHDbJ5PnPpUv3v+HFJUlgmU1rcixbVgRUr7Mo7hYSoU0jIbc+1dtbsTB/fanmGnRrS3dqX4Pr1FVy/vl29W68nO+cD8GgjUAAAAAAeAm998omktOkDAPAoIFAAAAAAHgIWsznT8qE9e2poz54PuDcAcGdsGwkAAAAAAAwjUAAAAAAAAIYRKAAAAAAAAMMIFAAAAAAAgGEECgAAAAAAwDACBQAAAAAAYBiBAgAAAAAAMIxAAQAAAAA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      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mat_con = np.array([\n",
    "    [true_neg, false_neg],\n",
    "    [false_pos, true_pos],\n",
    "])\n",
    "fig, px = plt.subplots(figsize=(8, 8))\n",
    "px.matshow(mat_con, cmap=plt.cm.YlOrRd, alpha=0.5)\n",
    "for m in range(mat_con.shape[0]):\n",
    "    for n in range(mat_con.shape[1]):\n",
    "        px.text(x=m,y=n,s=mat_con[m, n], va='center', ha='center', size='xx-large')\n",
    "   \n",
    "img = plt.imread('confusion_matrix.png')\n",
    "newax = fig.add_axes([0.9,0.2,1,0.6], anchor='NE', zorder=1)\n",
    "newax.imshow(img)\n",
    "newax.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "threatened-setup",
   "metadata": {},
   "source": [
    "## The same but using sklearn (results better due to usage of advanced techniques (lbfgs))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "functional-lover",
   "metadata": {},
   "outputs": [],
   "source": [
    "# skleran \n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "liable-blackberry",
   "metadata": {},
   "outputs": [],
   "source": [
    "n = encoded.shape[1]\n",
    "x_train = train.iloc[:, :n-1].to_numpy()\n",
    "x_test = test.iloc[:, :n-1].to_numpy()\n",
    "m = x_train.shape[0]\n",
    "y_train = train.iloc[:, n-1].to_numpy()\n",
    "y_test = test.iloc[:, n-1].to_numpy()\n",
    "\n",
    "model = LogisticRegression(random_state=0, max_iter=500).fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "legendary-walter",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.5544193559198427"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preds = model.predict(x_test)\n",
    "C = -np.sum( y_test*np.log1p(preds) + (1-y_test)*np.log1p(1-preds) )/x_test.shape[0]\n",
    "C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "cosmetic-metropolitan",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7998580553584103"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.score(x_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "absolute-ballot",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[929,  99],\n",
       "       [183, 198]])"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat_con = confusion_matrix(y_test, preds)\n",
    "mat_con"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "ranking-horizontal",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, px = plt.subplots(figsize=(8, 8))\n",
    "px.matshow(mat_con, cmap=plt.cm.YlOrRd, alpha=0.5)\n",
    "for m in range(mat_con.shape[0]):\n",
    "    for n in range(mat_con.shape[1]):\n",
    "        px.text(x=m,y=n,s=mat_con[m, n], va='center', ha='center', size='xx-large')\n",
    "   \n",
    "img = plt.imread('confusion_matrix.png')\n",
    "newax = fig.add_axes([0.9,0.2,1,0.6], anchor='NE', zorder=1)\n",
    "newax.imshow(img)\n",
    "newax.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "fallen-eating",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.557913956445729"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preds = model.predict(x_train)\n",
    "C = -np.sum( y_train*np.log1p(preds) + (1-y_train)*np.log1p(1-preds) )/x_train.shape[0]\n",
    "C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "communist-hardware",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8048996982069945"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.score(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "pleasant-prisoner",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3737,  408],\n",
       "       [ 691,  797]])"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat_con = confusion_matrix(y_train, preds)\n",
    "mat_con"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "ranging-nudist",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bN5e/n58+jI/XngMHNHXcOP1ZWKhrOnRw+IR9286d8u/TR7kpKTqWm6s7hj+k9R99rE++/lqRkyfr9/XrlXf8uPo+M0Gz//20mnp5lbjuJ1Onys3fX3ErV2rxG/+/vTuPi6pc/Dj+HcpRbFAJxSuKoKmYSmHirkUpRgqVirdM0co18yLdshUjbya5JVre3BUsV8wbbuSSaKlZY1bKNdOfiqYiCnqVXDDh9wcyMg4oRzEUP+/Xi9dr5jnnPOc5w7Cc7zzLRLttFn9/hYWE6NOoKHUOD9cGq1XpmzbJrVUr1fOpq82zYtW+X199t+0nZVqtat+vr5J379GRpCQdy8jQw88/r50JCeoSGKjIiRPVMyRE1uRkDRw+XD1DQvTEgAGKi45Wl8BAvTZmjCYvWKDugYGy+Pvrozfe0IghQ+Qb2lV/Zl3QzoQE+QQHa8u8eapZrZos/v4aER6uiF697Np88PBhjRgypNDX1svDQ22bNLE9d7FYtDQpqcCeCBUsFkVOnOhwDgB/HQIFAACAv8j3P2xV7VrekiSLi0U/btumBg0aKDExUTNnzlSvSzdG1m3bVLVqVUlSesYJ1fT01JixY203//l7MBTmu20/2R7X86krSerTp4+eeLqzrXeCr29DXbhwQWXKlCmuSyy1vDw8bI/d780dptIzJESnMjM1b/Vq/bZnj8Mx3jVqqJa3l3xDu2pMxCvaGBunu5ycNHD4cNXy9tLoGTMkSQ83ekBDoqMdAoM8+1atkv+zz9j1QriYnS1PDw/V9PBQ9LRpaubrqw2Xwgyz2azNs2IlSWumTdf9Tz5peyxJid9+qzWbN+vMubNXHTIQFhKiflFR6hIYqMkLFiguOlrW5GS1aOyn9JMnFT1tmh5v3kKTFyyQJJ3OzFTjrl01bODAQodNtGjsp3Jmc6GvbRVXV7ttv3/9tdr0eUG1OnQotJ0ASg6BAgAAwF+kWdMm2vDtJofytLQ0VahQwfbcNd9NVXx8vD799FOFh4drzrw4zZ4eK09Pz2ueq127dpJyhzuEheVOXnfqzP80e9ZMu/1OnDghd3f367qeO0n+T83znMrMVK0OHXQ+K8vW0yS/cmazvp46TS3Deio0IkIuFouOJCVJko4fT1dcvk/m/erVK/TcVe69V+OHvq4h0dG2sj/OnNHJU6fs6nCvXFmSZDbbB0SV3HLfT9bkZA0Y8b527d6jwFatVNnN7arX3Cc0VHMu1e9isajjI48o6fvvtTslRYeOXh5S43kpEIiPidGERQsUOXGiFqxbq1nDolS/dm27OsuUd3Y4T0GvbZ67nJz08WuvK6A3EzACtyLmUAAAAChhQUFBmr9wnu35Z599Znv8/Y/fac2aNcrJyVE5pzJq0bx5kepcsmSJXnktQsGdOmro0KGSpEcfDdCs2bHau2+/9u7br5ZtWxEm3ACf4GClb9qkTKtVW+fNd9ie+O236jU8SnuWr1Cm1apZI0YoJi5OPnXryGwuo50JCdqZkKCvpkzRo9f4vnYJDNSPv+60Pc+b1HDL3LnamZCgDbNnq3rV3O9lesYJ27wJ1uRkbd+eLEkK6N1bYU90VKbVatcbwrls2QLP6d+woUaEhysmLk5LJ01SObNZAc2aqa6Xl63tU6OiVN/bW5K0ZvNmrZzwsTKtVt1zdxm17tnToc79+1Kuep2FteNvVXmfouRkZ2fr8O+Ok4MacaPH36rooQAAAFDC3N3ddSL9pEwmk2p5e8lcpoySk3NvAhfNXaTRI8eqlreXJGn7jh12x3YKCpbJZFLb1i1lLlfeVu7i4qKYcRPsbsRGfTBGld3uVYUKFXT27Fk1bOT7F1xd6TXpnXfk1qqV3CtX1slTpxy2B7Vpoy3bt6taQIDM5jJKzzihTKtVEb16KXLCBLm1aiWz2azTmZlFWlkhZdVquyUdw3v0kEdAgDw9PHTw8GEN7dNHkmRduFDdXh+q0IgIRYSFyeVS+BASEKDIiRO17JsNOpGZqUcfaqJNP/2koDZt5OvbUBZ/fyXFxtqdM6JXL1n8/W3tK2c2q0rFSrL4+8vTw0MnJdVzNgAAF8pJREFUT53SpHfekSQt/+YbTV6wwNZjYWO+YCzPwcOH9cXq1eoSGFiUl9hmz/IVBS5nWVDPEBRNz6dy5145dfyksi5cUOVqVSRJn315fcvZFiaoWbCtbkn6ZesvOp+VpV1p2w3X1ar+w2pwf31NXzJVD9Rooi+TFqtWHW/5uPtq2/4tKl++/LUruQ5+NZtq7rI4TRs/S7v37JYk/bDZqqYtc9+TdevUlbu7u2LGTXA4dsfvP6qMuYw2rvtOnbo+ftPaWFIIFEqxr9d9p3ZBub8odicnqk4dL9u2P//8U9Gjp2rm7C90JPWYvL2qa/BLPfTyS8/JZDLZ1XPgwGEN/2CSvl63RalHj6va36oosF0rRb41UJ6ejpMHAaXV8/2HKfazhEK3j4garHfe6CdJSjlwWG9HfaxVazfr9Ok/5FPPW68M7qnnw5667joB3P7GjXf8ZzPPmjVrtH79eq1fv15vvfWWbV6Dn3/ZrlWrVik5OdlWfuHCBf1jULgkqWvXroqNjdU999yj+++/367OpKQkValSxa5s3/4UjR8/Xs7OzraeCyhcj+BgtXnooQK3dQkM1IEjR1TZ1VWPt26tlEtzHNxbqZLCL306H/XSS6p4zz2ScgOGPCOGDFFlV1eVd3bWw4V0+Z8SOcyhbOWUKbZ5Bt7q1089goP1+bJl6tyunW14Qf3atbU9frG+2bpVbZs00aeX5jiYN3asEr/9Vtt27tTrffrkDpu4NB/HVx9PUsK6darn5aWVU6Y4nDO/eWPHypqcrNWbNqlv166qcmlOiW3x8Vqxfr127d+vV3r3dpgrQZL+VtVdy9avV5fAQLVt0sSh7jwuFss123EsI0NhT3Qs8HhcW15wkLR6vf4veb/6RNy8YSX5Q4p9e/arR3AvnUg/IVc316sc5WjTrxtsj89nZdkeX084YUSbtm3VyK+hGvk1tJX5uPvaXdeno3LnKIl4dYgsrs46tD9Vs6bP1n8WLFO3sM7q2uMpTXj/33olavBNbetfzXQzZvb1b9Iox7o5vtjrRdFlZWXpQf/OOvh7qv7444xDoNDvpWGaPjNe/V7spmZNfbVqzSYtWpyo4e8O1rvvvGzbLz39hBo99KTOn7+gQQOelbdXde1I3q0p0xfKza2SkrctVcWKLiVxiXe2i1nX3gfFbvOWn/V/ew86lE+YNFfWH5O1deN8PdT4fh06dFRNWnfXufNZ+sfAZ1Xtb1W0dMV6Ja7eqPGjhypicE/DdeKv5Vnn0cMHD6VXv7K8ffv2OWvWrCmJJuE6xMXFSZJtokPc+tq3b68vR40q6Wbc1vJWm2jR2E8z//W+Hh8wQCdPnbLN3VDSzmVlqXFoqHYmFB6mF7WeRp2f1p7lK4qpZcXnqTfeUKeuQeoUGlTSTSmSKwOFHT8lq2uHZ1XWbJaHRzV9kbRQY4bFKGrc25KkJ1t3VsLGJZKkRXOWKPLVdyXl9hbJK88vqFmwEr9fZlc2fvgnatzKVwGBj2hGTKxGjxxrV8eFrAsa0nuo1q5dK0lq27qlpi+Zauuh4OJaSSuWrZSUGybk9VBo7N3cLlzwcffV4lXzVd3TQy3uf1iSVNZs1i+/b7Vd+4AeuTf4LhaLrHs3O7R/+KsjNWzMm3Jysp8twMfd1+5cn46arphxE7R41Xxb8ODj7mtre97zEeP+pW5hna/2LSlxy+MTtXxxovL9z2MqbF96KJRS42JmK+PE/9TvxVDFfBxnt+3nX37V9JnxeiW8tz4a86Ykqe+L3dSte45Gjpqqfi92U7Vqud0jFyxaqdTU4/oyfpKeDHnMVkct7xqKeC1aq9ZsVLeut8cvS+BGtWz+oFo2f9Cu7MyZsxoUMVK+jerabvyjx85Q2rEMbfw61rb/oAHP6MnQcEUO/0Rh3YPl5lbJUJ0AABTFXU5OyrRadTE7W5u2bbvhG/fiVs5s1s6EBB3LyLD1bLgeO3bv1uY5jkMqUHzybrrPnDlT6D6fjP7EdlOdtHq9Fs1ZUuDNct6n95I0/7N5Sj2apl1R29Xe73FJsqvj01HTlZaWprVr19rKZ8TYD8UZP3O0VrivVOKmpXblkSPe1JaNP6h566ba8VOyIke8qUZ+DR1u/h/xbad1P6/WgB6DbeU7fkousNfE3DnzbGFKUbz36vvKPJ2pU5eGQb0z5vKxbVu31PgPxt/ygYIRTMpYCqWkHNKI6Mn6cMQ/C+w9sGBRbpo3ZHCYXfmQwWE6fz5L/0lYays7dfoPSZKHh/1EOHnP7ylgpl7gTrIk4WudPv2HevcIsZVt2Pij7qvt6RAUhD0XrD/+OKv/LP3acJ0AABhxl5PTVVdPKGk3EiZIuRM13mgduDFnzpyRZ+2a2rLxB23Z+IMk6actPxe4b8y4CbavihUqKHJE7oeaBw8fVvuOl5cEfbhdW2397nv5t8wdZvTh2+N05syZIg/HCO7aUYlfrJYkLZ7zpYK7Xh4Sk9fOLRt/UOrRNKXsPSCfunXUt3N/LZqzRI38GhoeglGQ7duTtW9/itIzTsjFYlGtOt62bVWreyg948QNn+NWcs1AwWQyzTSZTGkmk2nHtfbFrSH8nyP1gG89Pd+r4OTLunWHqlatLC8v+968zZr6ysnJSVu3JdvKHgvInXH4H6+M0KbN23To0FGtXrNR77wboxbNH1SHwNY370KA20Ds5wm6++671fPZYFtZVtYFlS9fzmHfvADO+uN/DdcJAABwK8i6cEGSdDLjf/Ly9JKnVw15etVQvfvr6bXhQwo8Zlfadu1K266dqT8rYeMShfXvYdtWNt8qI05OTjp56pQ6hQZpV9p2Bf89SP27vywfd19lZ2dfs22ubq6aO2eeklav19w58+wCgrx2enrV0LofV6lGzepK2LhEY6aPUnlnZ7Wq/7CWxyde78tis3jVfNv1fr9n4w3Xd6srSg+F2ZLo036bWLZ8nZatSNInMcMcJlfMc/hImqp7OC69Yzab5eZWSYcOXV5XuFnTBzRpwjD9umufWgc8pxq1A9ShU1/51Kul1Stm6O67GTWDO9ehQ0e1dt33erx9S1Wtenktb5+63tr1236lph6323/dhtz0/tDhNBWmsDoBAKXHS8OHF/h1s8954NKkkS8NHy5rcvI1jgBylS9fXl8tv3yjvW9/7tKfHjWqKX7hYnnUqCaPGtU05t3x2rRuy1XrunIegufCumvypNzJNi9kXVDfzv313rhheuXF1+Xj7qtGfg0Vt2SGfH0b6uKfFx3qSzt6zKFs4MsD9NqANzXw5QG2srJms5ydy8mjRjVlHM/QwGcG6a6775KPu68qulZUp9Agjfz4faX+ftShvrIFTC5aVFde79bvrfL1bVjI3rena94N5uTkbDCZTN43vym4UWfPnlP4P0eq7wuhavJQ4W/Us2fPq0IFS4HbypUrq7PnztmVeVRzV4tmD6pD+1a6r3ZN/bJjl8Z8NFMhXQZpxZdT5Ozs+EkscCeYM2+ZsrOzHVZueHnAM0pYnqSuz72qMSNfUbW/VdbSFes1efoiSdKZs+cKqu6qdQIASo85S5cWWP5pVNRNPeeQsDDb48BWreTfsHTd2ODmSc84ob6d++v3Q4dtSyVKUtOW/gpt96x87q+vFctWavzM0YbqHfp+hLb/9It6PvWCDu49oNSjaZruN1Xhbw/Slk3faVD3CO39vz3atz9FZcxlHI7v98xA21wPeZ7uEazJk6bo6R6Xe3pGx3ygwKYd1TagrdauWqu5y+Lk5OSkF/o+r44tnlSTZv5a+p+l+u63bxzO0axp8Q0d2rc/xS7oKA34eLkU+eDDyTr5v9P64F8RV93P2bmszp8veJWAc+fOy7nc5YDgi/+s0jM9XtVPP3yhhg3qSpKeDHlMD/k1UKenB2ry1Pl6ZcjzxXYNwO0kbu4yubpWUEjHR+zKO7RvpSkfD9PrkTFq/VjumL9KlVz075i31atvpFwsha8/XFidAJCfyWTSzVipC3+NTKtVktS+X1/tTklRyqrVRT72wJEjci5b1mH+gMLKjTqXlaW09HTVrFbw0uBXTqZ44MgRu32PZWSorNmsChbHD69udCJG3BwBgY8oIPDy/x2N/Bo6LMNY2LKM+ZdN/OCT9wrc58oVHvIrX7684tfOtz3PG9ZQq4633RKRefKX5W9T/se16ng7tLdTaMGrbrw58lW9OfJVSdL7E9916FEgSZ8umKThr450mJjxynO89EZfvfRG36sOzWjXrl2pWzay2AIFk8nUX1J/SapZ06O4qkURHT6cprHjZyniH7108uQpnTyZO6toRsb/JEkHDh7RXXfdpVq1asijmru2J//mUEdWVpbS00/Kw+PyetUTPpmjunW8bGFCnieCHlb58s7a8K2VQAF3pB+sO7Tz170a1P8ZlS3r2BWuf59Q9eoRol+2/6aL2dnye8BHKQdyu5rWq+vlsH9R6gRwZzt9+rQyMjJsz1NScrsde3kV/DsFtx+Lf+4nv5lWq37du1f+f/+7PnrjDaWfPKkPpkyRi8Wie+4pr9SjaXK711Upq1bblon0qVtHx9PTlZ5xwhZYGPViZKQWJiaqlreX9u1PUVx0tLoEBurFyEit/PZbnc7MlCRNjorSwOHD5WKx6HRmpkaEh0uSIidOtNXlYrFo6aRJ8m/YUBZ/f9u+/126tNCwAijohr6kz13GXEa79+zWh2+Ps4UP11NPz6desAtgSoti+47l5ORMzcnJ8c/JyfGvUvnGZ8eEMWnH0nX+fJZGjZ2uug2DbF8f/zt3OZ12QS+ocfMukqQmDzVUaupxHThw2K6OH6w7lJ2drSaNL3d/S009rosXHccr5eTkKDs7Wxcu/HkTrwq4dcV+nrsM19VWYihXrqyaNfVVy+YPytm5nFat3SRJ6tCu1XXXCeDONXnyZHl7e8vb21uS7B6jdMg/VnvBV19Jkp594glbWYsHHtCe5StyQ4ZLM8Wv3pT7t2XrvPnatWz5DZ1/YWKihvbpo+3xi/X3oCC9HjNeFy992no6M1MhAQGKi4627V+5sptWTpmiHsHBen/yZPnUraP/Ll2qlVOm6HRmpgaMeN+2L2ECbmejJ42U71WGlBfFU6FPFlNrbi0MeSglannX0KJ5MQ7lC+MTtWhxoj4eH6manrm/wP8eGqQPx0zTxEmfaeyo1237Tpw0R2ZzGT39ZHtbWX2f2lq6fJ22fP+zmjd7MF+9K3Xu3Hn5N2l0E68KuDVlZV3Q/PivdH/92mrW1LdIxxw5ckwfjp2lJo0b6LGAZsVSJ4A7S6dOnVS1alVJUu/evRUbG3uNI3C7+Xz0aIVGRMianKwxM2ZIkt3QgdiRIyVJ/bt10z9HjZIkTVm4UNLl3g2SZE1Ovu75EcbMmGE7tyR9ufbycuLzxo6VJH12aQ6If7/1tm1pyvNZWVo3bboqWCy20GDX7j22Y93udSVMwG3Lo0Y1eYTe2Pu3W1jBK/Dd7q4ZKJhMpnmSAiRVNplMv0uKysnJmXH1o/BXq1jRRaFdHnco35G8W5IU1KGN6tTJ7RLZ2K+BXny+iz6aMFunT/+hZk19tWrNRi2MT1RU5MvyyLcCxBuv9dXKr75RYMc+GjSgu2rX8tQv23dp6oxFqlatigYN6P7XXCBwC1m2Yr3S009qaCFrIqemHtcTTw/S0yGPqUZ1dx04mKopM+KVoxx9NnNkgSuwXKtOAGjQoIEaNGggKTdQ6NWrVwm3CMUtqE0bRYSF6dnXh0qSBj7zjN325Zs3q3tgoK3XgCTd5+mpDWaz0i/1VLiRMEGSrRfBr3v3ysPdXRUsFi1bv15u9zr2QK7ial+W176CVHZj5SKgNCrKKg/cMZZCkz95TzU9PTQr7gvNnrNE3l7VNWHc2/rHyz3t9mvVsrGsmxfpXx/8W/MWLteRI8fl5lZR3Z/pqPejwuXuzh8H3HliP18qJycnhXUPLnC7xVJetWvV0LRZi5V2LEOV3VwV/MTDeu+dl1SjRtXrqhMA8mvXrl1JNwE3Sc+QEMXMmSNJerZjR7ttb44Zrcb33acJl7ZL0lOPPabJCxboVGamzmdlKaB3bx3ftEnlDC51lxdSDImO1tT33tPg6JHalvxf/bqs8An18nOxWPTmmNG6eO6cDqamSpJCAgIMtQHA7YchD6Xce8MG671hjjOJlilTRlGRLysq8uVr1vGAr4/i50+4Gc0DbktfLrr6z4PFUl6L531UrHUCQH5r1qwp6SagGPjV81GVipXsyurXri1JGhEe7tDT4KvJU9Q5IkJ3m8vocFKSJKltkyaaHBWl5s89J0lKio0tMExo0dhP5Z2dbY+vXG3hLicnZVqt6hweroeff171vb1tvR4eqFfPblnxyq6udvVJ0pGkJL02ZozGz/1c5nJldTgpyTZco0VjP9Wt4Wn49QFw6yNQAAAAAErA2KFD7Z5PXbRIv+3fL0mKKGBIi1ulStqZkOBQ3jMkRD1Drj6h75pp0wt8fKUl+VZqyHNlW4LatFFQmzYO+115PUU5H4DbG4ECAAAAcAvIm2jRJd9EjABwKyNQAAAAAG4BmVZrgeVv9eunt/r1+4tbAwDX5lTSDQAAAAAAALcfAgUAAAAAAGAYgQIAAAAAADCMQAEAAAAAABhGoAAAAAAAAAwjUAAAAAAAAIYRKAAAAAAAAMMIFAAAAAAAgGEECgAAAAAAwDACBQAAAAAAYBiBAgAAAAAAMIxAAQAAAAAAGEagAAAAAAAADCNQAAAAAAAAhhEoAAAAAAAAwwgUAAAAAACAYQQKAAAAAADAMAIFAAAAAABgGIECAAAAAAAwjEABAAAAAAAYRqAAAAAAAAAMI1AAAAAAAACGESgAAAAAAADDCBQAAAAAAIBhBAoAAAAAAMAwAgUAAAAAAGAYgQIAAAAAADCMQAEAAAAAABhGoAAAAAAAAAwjUAAAAAAAAIYRKAAAAAAAAMPuLukGAABwO4mLiyvpJqCItv3yY+4DvmW3lXmrV5d0E4Ab9lvyHkmJJd0M4Lrkvn+LhkABAIAi8vVrVNJNgAEeVauXdBNgkK9fI5k9PEq6GcAN8fVrJI+q1eV2j3tJNwW4LrW9clSuXLki7WvKyckp9gb4N2mUY90cX+z1ArjkYlZJtwAo1TzrPHr44KH0gu5Gi/+PJgAAwK3NVNgGeigAAFB0hf5BBQAAuNMwKSMAAAAAADCMQAEAAAAAABhGoAAAAAAAAAwjUAAAAAAAAIYRKAAAAAAAAMMIFAAAAAAAgGEECgAAAAAAwDACBQAAAAAAYBiBAgAAAAAAMIxAAQAAAAAAGEagAAAAAAAADCNQAAAAAAAAhhEoAAAAAAAAwwgUAAAAAACAYQQKAAAAAADAMAIFAAAAAABgGIECAAAAAAAwjEABAAAAAAAYRqAAAAAAAAAMI1AAAAAAAACGESgAAAAAAADDCBQAAAAAAIBhBAoAAAAAAMAwAgUAAAAAAGAYgQIAAAAAADCMQAEAAAAAABhGoAAAAAAAAAwjUAAAAAAAAIYRKAAAAAAAAMMIFAAAAAAAgGEECgAAAAAAwDACBQAAAAAAYBiBAgAAAAAAMIxAAQAAAAAAGEagAAAAAAAADCNQAAAAAAAAhhEoAAAAAAAAwwgUAAAAAACAYQQKAAAAAADAMAIFAAAAAABgGIECAAAAAAAwjEABAAAAAAAYRqAAAAAAAAAMI1AAAAAAAACGESgAAAAAAADDCBQAAAAAAIBhBAoAAAAAAMAwAgUAAAAAAGAYgQIAAAAAADCMQAEAAAAAABhGoAAAAAAAAAwjUAAAAAAAAIYRKAAAAAAAAMMIFAAAAAAAgGEECgAAAAAAwDACBQAAAAAAYBiBAgAAAAAAMIxAAQAAAAAAGEagAAAAAAAADCNQAAAAAAAAhhEoAAAAAAAAwwgUAAAAAACAYQQKAAAAAADAMAIFAAAAAABgmCknJ6f4KzWZjklKKfaKcbNUlnS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      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, px = plt.subplots(figsize=(8, 8))\n",
    "px.matshow(mat_con, cmap=plt.cm.YlOrRd, alpha=0.5)\n",
    "for m in range(mat_con.shape[0]):\n",
    "    for n in range(mat_con.shape[1]):\n",
    "        px.text(x=m,y=n,s=mat_con[m, n], va='center', ha='center', size='xx-large')\n",
    "   \n",
    "img = plt.imread('confusion_matrix.png')\n",
    "newax = fig.add_axes([0.9,0.2,1,0.6], anchor='NE', zorder=1)\n",
    "newax.imshow(img)\n",
    "newax.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "trained-experience",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}