3 - Modelos de Machine Learning/Alura Challenge Data Science - Semana3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Alura Challenge Data Science - Semana 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exterminando o futuro: Criando modelos de ML e compartilhando com os humanos o projeto final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importando bibliotecas\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Configurações de exibição\n",
    "\n",
    "pd.set_option(\"display.max_columns\", 100)\n",
    "pd.set_option(\"display.max_colwidth\", None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\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>ClienteId</th>\n",
       "      <th>ClienteCancelado</th>\n",
       "      <th>Gênero</th>\n",
       "      <th>Idoso</th>\n",
       "      <th>Parceiro</th>\n",
       "      <th>Dependentes</th>\n",
       "      <th>TempoContrato</th>\n",
       "      <th>ServiçoTelefone</th>\n",
       "      <th>MultiplasLinhas</th>\n",
       "      <th>ServiçoInternet</th>\n",
       "      <th>SegurançaOnline</th>\n",
       "      <th>BackupOnline</th>\n",
       "      <th>ProteçãoDispositivo</th>\n",
       "      <th>SuporteTecnico</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingFilmes</th>\n",
       "      <th>Contrato</th>\n",
       "      <th>FaturaSemPapel</th>\n",
       "      <th>FormaPagamento</th>\n",
       "      <th>ContasDiarias</th>\n",
       "      <th>CobrançaMensal</th>\n",
       "      <th>CobrançaTotal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0002-ORFBO</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>2.19</td>\n",
       "      <td>65.6</td>\n",
       "      <td>593.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0003-MKNFE</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>2.00</td>\n",
       "      <td>59.9</td>\n",
       "      <td>542.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0004-TLHLJ</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>2.46</td>\n",
       "      <td>73.9</td>\n",
       "      <td>280.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0011-IGKFF</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>13</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>3.27</td>\n",
       "      <td>98.0</td>\n",
       "      <td>1237.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0013-EXCHZ</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>2.80</td>\n",
       "      <td>83.9</td>\n",
       "      <td>267.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ClienteId ClienteCancelado  Gênero Idoso Parceiro Dependentes  \\\n",
       "0  0002-ORFBO               No  Female    No      Yes         Yes   \n",
       "1  0003-MKNFE               No    Male    No       No          No   \n",
       "2  0004-TLHLJ              Yes    Male    No       No          No   \n",
       "3  0011-IGKFF              Yes    Male   Yes      Yes          No   \n",
       "4  0013-EXCHZ              Yes  Female   Yes      Yes          No   \n",
       "\n",
       "   TempoContrato ServiçoTelefone MultiplasLinhas ServiçoInternet  \\\n",
       "0              9             Yes              No             DSL   \n",
       "1              9             Yes             Yes             DSL   \n",
       "2              4             Yes              No     Fiber optic   \n",
       "3             13             Yes              No     Fiber optic   \n",
       "4              3             Yes              No     Fiber optic   \n",
       "\n",
       "  SegurançaOnline BackupOnline ProteçãoDispositivo SuporteTecnico StreamingTV  \\\n",
       "0              No          Yes                  No            Yes         Yes   \n",
       "1              No           No                  No             No          No   \n",
       "2              No           No                 Yes             No          No   \n",
       "3              No          Yes                 Yes             No         Yes   \n",
       "4              No           No                  No            Yes         Yes   \n",
       "\n",
       "  StreamingFilmes        Contrato FaturaSemPapel    FormaPagamento  \\\n",
       "0              No        One year            Yes      Mailed check   \n",
       "1             Yes  Month-to-month             No      Mailed check   \n",
       "2              No  Month-to-month            Yes  Electronic check   \n",
       "3             Yes  Month-to-month            Yes  Electronic check   \n",
       "4              No  Month-to-month            Yes      Mailed check   \n",
       "\n",
       "   ContasDiarias  CobrançaMensal  CobrançaTotal  \n",
       "0           2.19            65.6         593.30  \n",
       "1           2.00            59.9         542.40  \n",
       "2           2.46            73.9         280.85  \n",
       "3           3.27            98.0        1237.85  \n",
       "4           2.80            83.9         267.40  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Importando base de dados e exibindo seus primeiros registros\n",
    "\n",
    "data = pd.read_csv('dataset/Telco-Customer-Churn-Tratado.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Encoding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Antes do encoding, irei alterar a coluna \"ClienteCancelado\", para notação: 0 = No e 1 = Yes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ClienteId</th>\n",
       "      <th>ClienteCancelado</th>\n",
       "      <th>Gênero</th>\n",
       "      <th>Idoso</th>\n",
       "      <th>Parceiro</th>\n",
       "      <th>Dependentes</th>\n",
       "      <th>TempoContrato</th>\n",
       "      <th>ServiçoTelefone</th>\n",
       "      <th>MultiplasLinhas</th>\n",
       "      <th>ServiçoInternet</th>\n",
       "      <th>SegurançaOnline</th>\n",
       "      <th>BackupOnline</th>\n",
       "      <th>ProteçãoDispositivo</th>\n",
       "      <th>SuporteTecnico</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingFilmes</th>\n",
       "      <th>Contrato</th>\n",
       "      <th>FaturaSemPapel</th>\n",
       "      <th>FormaPagamento</th>\n",
       "      <th>ContasDiarias</th>\n",
       "      <th>CobrançaMensal</th>\n",
       "      <th>CobrançaTotal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0002-ORFBO</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>2.19</td>\n",
       "      <td>65.60</td>\n",
       "      <td>593.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0003-MKNFE</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>2.00</td>\n",
       "      <td>59.90</td>\n",
       "      <td>542.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0004-TLHLJ</td>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>2.46</td>\n",
       "      <td>73.90</td>\n",
       "      <td>280.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0011-IGKFF</td>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>13</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>3.27</td>\n",
       "      <td>98.00</td>\n",
       "      <td>1237.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0013-EXCHZ</td>\n",
       "      <td>1</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>2.80</td>\n",
       "      <td>83.90</td>\n",
       "      <td>267.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0013-MHZWF</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>2.31</td>\n",
       "      <td>69.40</td>\n",
       "      <td>571.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0013-SMEOE</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>71</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>3.66</td>\n",
       "      <td>109.70</td>\n",
       "      <td>7904.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0014-BMAQU</td>\n",
       "      <td>0</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>63</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Credit card (automatic)</td>\n",
       "      <td>2.82</td>\n",
       "      <td>84.65</td>\n",
       "      <td>5377.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0015-UOCOJ</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>7</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>1.61</td>\n",
       "      <td>48.20</td>\n",
       "      <td>340.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0016-QLJIS</td>\n",
       "      <td>0</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>65</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Two year</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>3.02</td>\n",
       "      <td>90.45</td>\n",
       "      <td>5957.90</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ClienteId  ClienteCancelado  Gênero Idoso Parceiro Dependentes  \\\n",
       "0  0002-ORFBO                 0  Female    No      Yes         Yes   \n",
       "1  0003-MKNFE                 0    Male    No       No          No   \n",
       "2  0004-TLHLJ                 1    Male    No       No          No   \n",
       "3  0011-IGKFF                 1    Male   Yes      Yes          No   \n",
       "4  0013-EXCHZ                 1  Female   Yes      Yes          No   \n",
       "5  0013-MHZWF                 0  Female    No       No         Yes   \n",
       "6  0013-SMEOE                 0  Female   Yes      Yes          No   \n",
       "7  0014-BMAQU                 0    Male    No      Yes          No   \n",
       "8  0015-UOCOJ                 0  Female   Yes       No          No   \n",
       "9  0016-QLJIS                 0  Female    No      Yes         Yes   \n",
       "\n",
       "   TempoContrato ServiçoTelefone MultiplasLinhas ServiçoInternet  \\\n",
       "0              9             Yes              No             DSL   \n",
       "1              9             Yes             Yes             DSL   \n",
       "2              4             Yes              No     Fiber optic   \n",
       "3             13             Yes              No     Fiber optic   \n",
       "4              3             Yes              No     Fiber optic   \n",
       "5              9             Yes              No             DSL   \n",
       "6             71             Yes              No     Fiber optic   \n",
       "7             63             Yes             Yes     Fiber optic   \n",
       "8              7             Yes              No             DSL   \n",
       "9             65             Yes             Yes             DSL   \n",
       "\n",
       "  SegurançaOnline BackupOnline ProteçãoDispositivo SuporteTecnico StreamingTV  \\\n",
       "0              No          Yes                  No            Yes         Yes   \n",
       "1              No           No                  No             No          No   \n",
       "2              No           No                 Yes             No          No   \n",
       "3              No          Yes                 Yes             No         Yes   \n",
       "4              No           No                  No            Yes         Yes   \n",
       "5              No           No                  No            Yes         Yes   \n",
       "6             Yes          Yes                 Yes            Yes         Yes   \n",
       "7             Yes           No                  No            Yes          No   \n",
       "8             Yes           No                  No             No          No   \n",
       "9             Yes          Yes                 Yes            Yes         Yes   \n",
       "\n",
       "  StreamingFilmes        Contrato FaturaSemPapel             FormaPagamento  \\\n",
       "0              No        One year            Yes               Mailed check   \n",
       "1             Yes  Month-to-month             No               Mailed check   \n",
       "2              No  Month-to-month            Yes           Electronic check   \n",
       "3             Yes  Month-to-month            Yes           Electronic check   \n",
       "4              No  Month-to-month            Yes               Mailed check   \n",
       "5             Yes  Month-to-month            Yes    Credit card (automatic)   \n",
       "6             Yes        Two year            Yes  Bank transfer (automatic)   \n",
       "7              No        Two year            Yes    Credit card (automatic)   \n",
       "8              No  Month-to-month            Yes           Electronic check   \n",
       "9             Yes        Two year            Yes               Mailed check   \n",
       "\n",
       "   ContasDiarias  CobrançaMensal  CobrançaTotal  \n",
       "0           2.19           65.60         593.30  \n",
       "1           2.00           59.90         542.40  \n",
       "2           2.46           73.90         280.85  \n",
       "3           3.27           98.00        1237.85  \n",
       "4           2.80           83.90         267.40  \n",
       "5           2.31           69.40         571.45  \n",
       "6           3.66          109.70        7904.25  \n",
       "7           2.82           84.65        5377.80  \n",
       "8           1.61           48.20         340.35  \n",
       "9           3.02           90.45        5957.90  "
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Feita a alteração, onde o '0' foi substituido por 'No', e '1' por 'Yes'\n",
    "\n",
    "for cliente in 'ClienteCancelado':\n",
    "    data['ClienteCancelado'] = data['ClienteCancelado'].replace({'No': 0, 'Yes': 1})\n",
    "\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "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",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ClienteId</th>\n",
       "      <th>ClienteCancelado</th>\n",
       "      <th>TempoContrato</th>\n",
       "      <th>ContasDiarias</th>\n",
       "      <th>CobrançaMensal</th>\n",
       "      <th>CobrançaTotal</th>\n",
       "      <th>Gênero_Female</th>\n",
       "      <th>Gênero_Male</th>\n",
       "      <th>Idoso_No</th>\n",
       "      <th>Idoso_Yes</th>\n",
       "      <th>Parceiro_No</th>\n",
       "      <th>Parceiro_Yes</th>\n",
       "      <th>Dependentes_No</th>\n",
       "      <th>Dependentes_Yes</th>\n",
       "      <th>ServiçoTelefone_No</th>\n",
       "      <th>ServiçoTelefone_Yes</th>\n",
       "      <th>MultiplasLinhas_No</th>\n",
       "      <th>MultiplasLinhas_No phone service</th>\n",
       "      <th>MultiplasLinhas_Yes</th>\n",
       "      <th>ServiçoInternet_DSL</th>\n",
       "      <th>ServiçoInternet_Fiber optic</th>\n",
       "      <th>ServiçoInternet_No</th>\n",
       "      <th>SegurançaOnline_No</th>\n",
       "      <th>SegurançaOnline_No internet service</th>\n",
       "      <th>SegurançaOnline_Yes</th>\n",
       "      <th>BackupOnline_No</th>\n",
       "      <th>BackupOnline_No internet service</th>\n",
       "      <th>BackupOnline_Yes</th>\n",
       "      <th>ProteçãoDispositivo_No</th>\n",
       "      <th>ProteçãoDispositivo_No internet service</th>\n",
       "      <th>ProteçãoDispositivo_Yes</th>\n",
       "      <th>SuporteTecnico_No</th>\n",
       "      <th>SuporteTecnico_No internet service</th>\n",
       "      <th>SuporteTecnico_Yes</th>\n",
       "      <th>StreamingTV_No</th>\n",
       "      <th>StreamingTV_No internet service</th>\n",
       "      <th>StreamingTV_Yes</th>\n",
       "      <th>StreamingFilmes_No</th>\n",
       "      <th>StreamingFilmes_No internet service</th>\n",
       "      <th>StreamingFilmes_Yes</th>\n",
       "      <th>Contrato_Month-to-month</th>\n",
       "      <th>Contrato_One year</th>\n",
       "      <th>Contrato_Two year</th>\n",
       "      <th>FaturaSemPapel_No</th>\n",
       "      <th>FaturaSemPapel_Yes</th>\n",
       "      <th>FormaPagamento_Bank transfer (automatic)</th>\n",
       "      <th>FormaPagamento_Credit card (automatic)</th>\n",
       "      <th>FormaPagamento_Electronic check</th>\n",
       "      <th>FormaPagamento_Mailed check</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0002-ORFBO</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2.19</td>\n",
       "      <td>65.6</td>\n",
       "      <td>593.30</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0003-MKNFE</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2.00</td>\n",
       "      <td>59.9</td>\n",
       "      <td>542.40</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0004-TLHLJ</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2.46</td>\n",
       "      <td>73.9</td>\n",
       "      <td>280.85</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0011-IGKFF</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>3.27</td>\n",
       "      <td>98.0</td>\n",
       "      <td>1237.85</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0013-EXCHZ</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.80</td>\n",
       "      <td>83.9</td>\n",
       "      <td>267.40</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ClienteId  ClienteCancelado  TempoContrato  ContasDiarias  CobrançaMensal  \\\n",
       "0  0002-ORFBO                 0              9           2.19            65.6   \n",
       "1  0003-MKNFE                 0              9           2.00            59.9   \n",
       "2  0004-TLHLJ                 1              4           2.46            73.9   \n",
       "3  0011-IGKFF                 1             13           3.27            98.0   \n",
       "4  0013-EXCHZ                 1              3           2.80            83.9   \n",
       "\n",
       "   CobrançaTotal  Gênero_Female  Gênero_Male  Idoso_No  Idoso_Yes  \\\n",
       "0         593.30              1            0         1          0   \n",
       "1         542.40              0            1         1          0   \n",
       "2         280.85              0            1         1          0   \n",
       "3        1237.85              0            1         0          1   \n",
       "4         267.40              1            0         0          1   \n",
       "\n",
       "   Parceiro_No  Parceiro_Yes  Dependentes_No  Dependentes_Yes  \\\n",
       "0            0             1               0                1   \n",
       "1            1             0               1                0   \n",
       "2            1             0               1                0   \n",
       "3            0             1               1                0   \n",
       "4            0             1               1                0   \n",
       "\n",
       "   ServiçoTelefone_No  ServiçoTelefone_Yes  MultiplasLinhas_No  \\\n",
       "0                   0                    1                   1   \n",
       "1                   0                    1                   0   \n",
       "2                   0                    1                   1   \n",
       "3                   0                    1                   1   \n",
       "4                   0                    1                   1   \n",
       "\n",
       "   MultiplasLinhas_No phone service  MultiplasLinhas_Yes  ServiçoInternet_DSL  \\\n",
       "0                                 0                    0                    1   \n",
       "1                                 0                    1                    1   \n",
       "2                                 0                    0                    0   \n",
       "3                                 0                    0                    0   \n",
       "4                                 0                    0                    0   \n",
       "\n",
       "   ServiçoInternet_Fiber optic  ServiçoInternet_No  SegurançaOnline_No  \\\n",
       "0                            0                   0                   1   \n",
       "1                            0                   0                   1   \n",
       "2                            1                   0                   1   \n",
       "3                            1                   0                   1   \n",
       "4                            1                   0                   1   \n",
       "\n",
       "   SegurançaOnline_No internet service  SegurançaOnline_Yes  BackupOnline_No  \\\n",
       "0                                    0                    0                0   \n",
       "1                                    0                    0                1   \n",
       "2                                    0                    0                1   \n",
       "3                                    0                    0                0   \n",
       "4                                    0                    0                1   \n",
       "\n",
       "   BackupOnline_No internet service  BackupOnline_Yes  ProteçãoDispositivo_No  \\\n",
       "0                                 0                 1                       1   \n",
       "1                                 0                 0                       1   \n",
       "2                                 0                 0                       0   \n",
       "3                                 0                 1                       0   \n",
       "4                                 0                 0                       1   \n",
       "\n",
       "   ProteçãoDispositivo_No internet service  ProteçãoDispositivo_Yes  \\\n",
       "0                                        0                        0   \n",
       "1                                        0                        0   \n",
       "2                                        0                        1   \n",
       "3                                        0                        1   \n",
       "4                                        0                        0   \n",
       "\n",
       "   SuporteTecnico_No  SuporteTecnico_No internet service  SuporteTecnico_Yes  \\\n",
       "0                  0                                   0                   1   \n",
       "1                  1                                   0                   0   \n",
       "2                  1                                   0                   0   \n",
       "3                  1                                   0                   0   \n",
       "4                  0                                   0                   1   \n",
       "\n",
       "   StreamingTV_No  StreamingTV_No internet service  StreamingTV_Yes  \\\n",
       "0               0                                0                1   \n",
       "1               1                                0                0   \n",
       "2               1                                0                0   \n",
       "3               0                                0                1   \n",
       "4               0                                0                1   \n",
       "\n",
       "   StreamingFilmes_No  StreamingFilmes_No internet service  \\\n",
       "0                   1                                    0   \n",
       "1                   0                                    0   \n",
       "2                   1                                    0   \n",
       "3                   0                                    0   \n",
       "4                   1                                    0   \n",
       "\n",
       "   StreamingFilmes_Yes  Contrato_Month-to-month  Contrato_One year  \\\n",
       "0                    0                        0                  1   \n",
       "1                    1                        1                  0   \n",
       "2                    0                        1                  0   \n",
       "3                    1                        1                  0   \n",
       "4                    0                        1                  0   \n",
       "\n",
       "   Contrato_Two year  FaturaSemPapel_No  FaturaSemPapel_Yes  \\\n",
       "0                  0                  0                   1   \n",
       "1                  0                  1                   0   \n",
       "2                  0                  0                   1   \n",
       "3                  0                  0                   1   \n",
       "4                  0                  0                   1   \n",
       "\n",
       "   FormaPagamento_Bank transfer (automatic)  \\\n",
       "0                                         0   \n",
       "1                                         0   \n",
       "2                                         0   \n",
       "3                                         0   \n",
       "4                                         0   \n",
       "\n",
       "   FormaPagamento_Credit card (automatic)  FormaPagamento_Electronic check  \\\n",
       "0                                       0                                0   \n",
       "1                                       0                                0   \n",
       "2                                       0                                1   \n",
       "3                                       0                                1   \n",
       "4                                       0                                0   \n",
       "\n",
       "   FormaPagamento_Mailed check  \n",
       "0                            1  \n",
       "1                            1  \n",
       "2                            0  \n",
       "3                            0  \n",
       "4                            1  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Será utilizado o método 'One-Hot-Enconding' para o encoding, pois com ele não criamos uma hierarquia\n",
    "\n",
    "categorias = ['Gênero', 'Idoso', 'Parceiro',\n",
    "              'Dependentes', 'ServiçoTelefone', 'MultiplasLinhas',\n",
    "              'ServiçoInternet', 'SegurançaOnline', 'BackupOnline',\n",
    "              'ProteçãoDispositivo', 'SuporteTecnico', 'StreamingTV',\n",
    "              'StreamingFilmes', 'Contrato', 'FaturaSemPapel', 'FormaPagamento']\n",
    "\n",
    "data = pd.get_dummies(data = data, columns = categorias)\n",
    "data.head()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Removendo variáveis que não irei utilizar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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>ClienteCancelado</th>\n",
       "      <th>TempoContrato</th>\n",
       "      <th>ContasDiarias</th>\n",
       "      <th>CobrançaMensal</th>\n",
       "      <th>CobrançaTotal</th>\n",
       "      <th>Gênero_Female</th>\n",
       "      <th>Gênero_Male</th>\n",
       "      <th>Idoso_No</th>\n",
       "      <th>Idoso_Yes</th>\n",
       "      <th>Parceiro_No</th>\n",
       "      <th>Parceiro_Yes</th>\n",
       "      <th>Dependentes_No</th>\n",
       "      <th>Dependentes_Yes</th>\n",
       "      <th>ServiçoTelefone_No</th>\n",
       "      <th>ServiçoTelefone_Yes</th>\n",
       "      <th>MultiplasLinhas_No</th>\n",
       "      <th>MultiplasLinhas_No phone service</th>\n",
       "      <th>MultiplasLinhas_Yes</th>\n",
       "      <th>ServiçoInternet_DSL</th>\n",
       "      <th>ServiçoInternet_Fiber optic</th>\n",
       "      <th>ServiçoInternet_No</th>\n",
       "      <th>SegurançaOnline_No</th>\n",
       "      <th>SegurançaOnline_No internet service</th>\n",
       "      <th>SegurançaOnline_Yes</th>\n",
       "      <th>BackupOnline_No</th>\n",
       "      <th>BackupOnline_No internet service</th>\n",
       "      <th>BackupOnline_Yes</th>\n",
       "      <th>ProteçãoDispositivo_No</th>\n",
       "      <th>ProteçãoDispositivo_No internet service</th>\n",
       "      <th>ProteçãoDispositivo_Yes</th>\n",
       "      <th>SuporteTecnico_No</th>\n",
       "      <th>SuporteTecnico_No internet service</th>\n",
       "      <th>SuporteTecnico_Yes</th>\n",
       "      <th>StreamingTV_No</th>\n",
       "      <th>StreamingTV_No internet service</th>\n",
       "      <th>StreamingTV_Yes</th>\n",
       "      <th>StreamingFilmes_No</th>\n",
       "      <th>StreamingFilmes_No internet service</th>\n",
       "      <th>StreamingFilmes_Yes</th>\n",
       "      <th>Contrato_Month-to-month</th>\n",
       "      <th>Contrato_One year</th>\n",
       "      <th>Contrato_Two year</th>\n",
       "      <th>FaturaSemPapel_No</th>\n",
       "      <th>FaturaSemPapel_Yes</th>\n",
       "      <th>FormaPagamento_Bank transfer (automatic)</th>\n",
       "      <th>FormaPagamento_Credit card (automatic)</th>\n",
       "      <th>FormaPagamento_Electronic check</th>\n",
       "      <th>FormaPagamento_Mailed check</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>9</td>\n",
       "      <td>2.19</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2.00</td>\n",
       "      <td>59.9</td>\n",
       "      <td>542.40</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2.46</td>\n",
       "      <td>73.9</td>\n",
       "      <td>280.85</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>3.27</td>\n",
       "      <td>98.0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.80</td>\n",
       "      <td>83.9</td>\n",
       "      <td>267.40</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ClienteCancelado  TempoContrato  ContasDiarias  CobrançaMensal  \\\n",
       "0                 0              9           2.19            65.6   \n",
       "1                 0              9           2.00            59.9   \n",
       "2                 1              4           2.46            73.9   \n",
       "3                 1             13           3.27            98.0   \n",
       "4                 1              3           2.80            83.9   \n",
       "\n",
       "   CobrançaTotal  Gênero_Female  Gênero_Male  Idoso_No  Idoso_Yes  \\\n",
       "0         593.30              1            0         1          0   \n",
       "1         542.40              0            1         1          0   \n",
       "2         280.85              0            1         1          0   \n",
       "3        1237.85              0            1         0          1   \n",
       "4         267.40              1            0         0          1   \n",
       "\n",
       "   Parceiro_No  Parceiro_Yes  Dependentes_No  Dependentes_Yes  \\\n",
       "0            0             1               0                1   \n",
       "1            1             0               1                0   \n",
       "2            1             0               1                0   \n",
       "3            0             1               1                0   \n",
       "4            0             1               1                0   \n",
       "\n",
       "   ServiçoTelefone_No  ServiçoTelefone_Yes  MultiplasLinhas_No  \\\n",
       "0                   0                    1                   1   \n",
       "1                   0                    1                   0   \n",
       "2                   0                    1                   1   \n",
       "3                   0                    1                   1   \n",
       "4                   0                    1                   1   \n",
       "\n",
       "   MultiplasLinhas_No phone service  MultiplasLinhas_Yes  ServiçoInternet_DSL  \\\n",
       "0                                 0                    0                    1   \n",
       "1                                 0                    1                    1   \n",
       "2                                 0                    0                    0   \n",
       "3                                 0                    0                    0   \n",
       "4                                 0                    0                    0   \n",
       "\n",
       "   ServiçoInternet_Fiber optic  ServiçoInternet_No  SegurançaOnline_No  \\\n",
       "0                            0                   0                   1   \n",
       "1                            0                   0                   1   \n",
       "2                            1                   0                   1   \n",
       "3                            1                   0                   1   \n",
       "4                            1                   0                   1   \n",
       "\n",
       "   SegurançaOnline_No internet service  SegurançaOnline_Yes  BackupOnline_No  \\\n",
       "0                                    0                    0                0   \n",
       "1                                    0                    0                1   \n",
       "2                                    0                    0                1   \n",
       "3                                    0                    0                0   \n",
       "4                                    0                    0                1   \n",
       "\n",
       "   BackupOnline_No internet service  BackupOnline_Yes  ProteçãoDispositivo_No  \\\n",
       "0                                 0                 1                       1   \n",
       "1                                 0                 0                       1   \n",
       "2                                 0                 0                       0   \n",
       "3                                 0                 1                       0   \n",
       "4                                 0                 0                       1   \n",
       "\n",
       "   ProteçãoDispositivo_No internet service  ProteçãoDispositivo_Yes  \\\n",
       "0                                        0                        0   \n",
       "1                                        0                        0   \n",
       "2                                        0                        1   \n",
       "3                                        0                        1   \n",
       "4                                        0                        0   \n",
       "\n",
       "   SuporteTecnico_No  SuporteTecnico_No internet service  SuporteTecnico_Yes  \\\n",
       "0                  0                                   0                   1   \n",
       "1                  1                                   0                   0   \n",
       "2                  1                                   0                   0   \n",
       "3                  1                                   0                   0   \n",
       "4                  0                                   0                   1   \n",
       "\n",
       "   StreamingTV_No  StreamingTV_No internet service  StreamingTV_Yes  \\\n",
       "0               0                                0                1   \n",
       "1               1                                0                0   \n",
       "2               1                                0                0   \n",
       "3               0                                0                1   \n",
       "4               0                                0                1   \n",
       "\n",
       "   StreamingFilmes_No  StreamingFilmes_No internet service  \\\n",
       "0                   1                                    0   \n",
       "1                   0                                    0   \n",
       "2                   1                                    0   \n",
       "3                   0                                    0   \n",
       "4                   1                                    0   \n",
       "\n",
       "   StreamingFilmes_Yes  Contrato_Month-to-month  Contrato_One year  \\\n",
       "0                    0                        0                  1   \n",
       "1                    1                        1                  0   \n",
       "2                    0                        1                  0   \n",
       "3                    1                        1                  0   \n",
       "4                    0                        1                  0   \n",
       "\n",
       "   Contrato_Two year  FaturaSemPapel_No  FaturaSemPapel_Yes  \\\n",
       "0                  0                  0                   1   \n",
       "1                  0                  1                   0   \n",
       "2                  0                  0                   1   \n",
       "3                  0                  0                   1   \n",
       "4                  0                  0                   1   \n",
       "\n",
       "   FormaPagamento_Bank transfer (automatic)  \\\n",
       "0                                         0   \n",
       "1                                         0   \n",
       "2                                         0   \n",
       "3                                         0   \n",
       "4                                         0   \n",
       "\n",
       "   FormaPagamento_Credit card (automatic)  FormaPagamento_Electronic check  \\\n",
       "0                                       0                                0   \n",
       "1                                       0                                0   \n",
       "2                                       0                                1   \n",
       "3                                       0                                1   \n",
       "4                                       0                                0   \n",
       "\n",
       "   FormaPagamento_Mailed check  \n",
       "0                            1  \n",
       "1                            1  \n",
       "2                            0  \n",
       "3                            0  \n",
       "4                            1  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = data.drop(['ClienteId'], axis = 1)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Verificar se a variável target está balanceada"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5174\n",
       "1    1869\n",
       "Name: ClienteCancelado, dtype: int64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.ClienteCancelado.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Existem 5174 clientes que tem contrato com a empresa e 1869 clientes que não possuem. O dataset não está balanceado.\n"
     ]
    }
   ],
   "source": [
    "print(f'Existem {data.ClienteCancelado.value_counts()[0]} clientes que tem contrato com a empresa e ' +\n",
    "      f'{data.ClienteCancelado.value_counts()[1]} clientes que não possuem. O dataset não está balanceado.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Irei utilizar a técnica de balanceamento de dados **oversampling**, que é basicamente duplicar, fazer a cópia dos nossos dados da classe minoritária até chegar no valor da classe majoritária. Então, ela faria cópia dos dados de 'churn', ou seja, criaria novos dados até chegarmos ao número de dados dos clientes com contrato. Para que não ocorra muitos dados idênticos, será utilizada a técnica SMOTE, que cria dados sintéticos próximos dos reais."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "from imblearn.over_sampling import SMOTE\n",
    "\n",
    "SEED = 25\n",
    "smote = SMOTE(random_state = SEED)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = data.drop('ClienteCancelado', axis = 1)\n",
    "y = data['ClienteCancelado']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_resampled, y_resampled = smote.fit_resample(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10347</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.687965</td>\n",
       "      <td>50.629654</td>\n",
       "      <td>50.629654</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10348 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ClienteCancelado  TempoContrato  ContasDiarias  CobrançaMensal  \\\n",
       "0                     0              9       2.190000       65.600000   \n",
       "1                     0              9       2.000000       59.900000   \n",
       "2                     1              4       2.460000       73.900000   \n",
       "3                     1             13       3.270000       98.000000   \n",
       "4                     1              3       2.800000       83.900000   \n",
       "...                 ...            ...            ...             ...   \n",
       "10343                 1             21       1.039973       31.277442   \n",
       "10344                 1             38       3.224635       96.689054   \n",
       "10345                 1              9       3.068459       92.049687   \n",
       "10346                 1              5       2.596265       77.815525   \n",
       "10347                 1              1       1.687965       50.629654   \n",
       "\n",
       "       CobrançaTotal  Gênero_Female  Gênero_Male  Idoso_No  Idoso_Yes  \\\n",
       "0         593.300000              1            0         1          0   \n",
       "1         542.400000              0            1         1          0   \n",
       "2         280.850000              0            1         1          0   \n",
       "3        1237.850000              0            1         0          1   \n",
       "4         267.400000              1            0         0          1   \n",
       "...              ...            ...          ...       ...        ...   \n",
       "10343     673.524300              0            0         1          0   \n",
       "10344    3752.442684              0            0         0          1   \n",
       "10345     860.055985              0            0         1          0   \n",
       "10346     414.502376              0            0         1          0   \n",
       "10347      50.629654              0            0         1          0   \n",
       "\n",
       "       Parceiro_No  Parceiro_Yes  Dependentes_No  Dependentes_Yes  \\\n",
       "0                0             1               0                1   \n",
       "1                1             0               1                0   \n",
       "2                1             0               1                0   \n",
       "3                0             1               1                0   \n",
       "4                0             1               1                0   \n",
       "...            ...           ...             ...              ...   \n",
       "10343            0             0               1                0   \n",
       "10344            1             0               1                0   \n",
       "10345            1             0               1                0   \n",
       "10346            1             0               1                0   \n",
       "10347            1             0               1                0   \n",
       "\n",
       "       ServiçoTelefone_No  ServiçoTelefone_Yes  MultiplasLinhas_No  \\\n",
       "0                       0                    1                   1   \n",
       "1                       0                    1                   0   \n",
       "2                       0                    1                   1   \n",
       "3                       0                    1                   1   \n",
       "4                       0                    1                   1   \n",
       "...                   ...                  ...                 ...   \n",
       "10343                   0                    0                   0   \n",
       "10344                   0                    1                   0   \n",
       "10345                   0                    1                   0   \n",
       "10346                   0                    1                   0   \n",
       "10347                   0                    1                   1   \n",
       "\n",
       "       MultiplasLinhas_No phone service  MultiplasLinhas_Yes  \\\n",
       "0                                     0                    0   \n",
       "1                                     0                    1   \n",
       "2                                     0                    0   \n",
       "3                                     0                    0   \n",
       "4                                     0                    0   \n",
       "...                                 ...                  ...   \n",
       "10343                                 0                    0   \n",
       "10344                                 0                    1   \n",
       "10345                                 0                    0   \n",
       "10346                                 0                    0   \n",
       "10347                                 0                    0   \n",
       "\n",
       "       ServiçoInternet_DSL  ServiçoInternet_Fiber optic  ServiçoInternet_No  \\\n",
       "0                        1                            0                   0   \n",
       "1                        1                            0                   0   \n",
       "2                        0                            1                   0   \n",
       "3                        0                            1                   0   \n",
       "4                        0                            1                   0   \n",
       "...                    ...                          ...                 ...   \n",
       "10343                    0                            0                   0   \n",
       "10344                    0                            1                   0   \n",
       "10345                    0                            1                   0   \n",
       "10346                    0                            1                   0   \n",
       "10347                    1                            0                   0   \n",
       "\n",
       "       SegurançaOnline_No  SegurançaOnline_No internet service  \\\n",
       "0                       1                                    0   \n",
       "1                       1                                    0   \n",
       "2                       1                                    0   \n",
       "3                       1                                    0   \n",
       "4                       1                                    0   \n",
       "...                   ...                                  ...   \n",
       "10343                   0                                    0   \n",
       "10344                   1                                    0   \n",
       "10345                   1                                    0   \n",
       "10346                   1                                    0   \n",
       "10347                   1                                    0   \n",
       "\n",
       "       SegurançaOnline_Yes  BackupOnline_No  BackupOnline_No internet service  \\\n",
       "0                        0                0                                 0   \n",
       "1                        0                1                                 0   \n",
       "2                        0                1                                 0   \n",
       "3                        0                0                                 0   \n",
       "4                        0                1                                 0   \n",
       "...                    ...              ...                               ...   \n",
       "10343                    0                0                                 0   \n",
       "10344                    0                1                                 0   \n",
       "10345                    0                1                                 0   \n",
       "10346                    0                1                                 0   \n",
       "10347                    0                0                                 0   \n",
       "\n",
       "       BackupOnline_Yes  ProteçãoDispositivo_No  \\\n",
       "0                     1                       1   \n",
       "1                     0                       1   \n",
       "2                     0                       0   \n",
       "3                     1                       0   \n",
       "4                     0                       1   \n",
       "...                 ...                     ...   \n",
       "10343                 0                       0   \n",
       "10344                 0                       1   \n",
       "10345                 0                       1   \n",
       "10346                 0                       1   \n",
       "10347                 1                       1   \n",
       "\n",
       "       ProteçãoDispositivo_No internet service  ProteçãoDispositivo_Yes  \\\n",
       "0                                            0                        0   \n",
       "1                                            0                        0   \n",
       "2                                            0                        1   \n",
       "3                                            0                        1   \n",
       "4                                            0                        0   \n",
       "...                                        ...                      ...   \n",
       "10343                                        0                        0   \n",
       "10344                                        0                        0   \n",
       "10345                                        0                        0   \n",
       "10346                                        0                        0   \n",
       "10347                                        0                        0   \n",
       "\n",
       "       SuporteTecnico_No  SuporteTecnico_No internet service  \\\n",
       "0                      0                                   0   \n",
       "1                      1                                   0   \n",
       "2                      1                                   0   \n",
       "3                      1                                   0   \n",
       "4                      0                                   0   \n",
       "...                  ...                                 ...   \n",
       "10343                  0                                   0   \n",
       "10344                  0                                   0   \n",
       "10345                  1                                   0   \n",
       "10346                  1                                   0   \n",
       "10347                  1                                   0   \n",
       "\n",
       "       SuporteTecnico_Yes  StreamingTV_No  StreamingTV_No internet service  \\\n",
       "0                       1               0                                0   \n",
       "1                       0               1                                0   \n",
       "2                       0               1                                0   \n",
       "3                       0               0                                0   \n",
       "4                       1               0                                0   \n",
       "...                   ...             ...                              ...   \n",
       "10343                   0               0                                0   \n",
       "10344                   0               0                                0   \n",
       "10345                   0               0                                0   \n",
       "10346                   0               0                                0   \n",
       "10347                   0               1                                0   \n",
       "\n",
       "       StreamingTV_Yes  StreamingFilmes_No  \\\n",
       "0                    1                   1   \n",
       "1                    0                   0   \n",
       "2                    0                   1   \n",
       "3                    1                   0   \n",
       "4                    1                   1   \n",
       "...                ...                 ...   \n",
       "10343                0                   0   \n",
       "10344                1                   0   \n",
       "10345                1                   0   \n",
       "10346                0                   1   \n",
       "10347                0                   1   \n",
       "\n",
       "       StreamingFilmes_No internet service  StreamingFilmes_Yes  \\\n",
       "0                                        0                    0   \n",
       "1                                        0                    1   \n",
       "2                                        0                    0   \n",
       "3                                        0                    1   \n",
       "4                                        0                    0   \n",
       "...                                    ...                  ...   \n",
       "10343                                    0                    0   \n",
       "10344                                    0                    1   \n",
       "10345                                    0                    1   \n",
       "10346                                    0                    0   \n",
       "10347                                    0                    0   \n",
       "\n",
       "       Contrato_Month-to-month  Contrato_One year  Contrato_Two year  \\\n",
       "0                            0                  1                  0   \n",
       "1                            1                  0                  0   \n",
       "2                            1                  0                  0   \n",
       "3                            1                  0                  0   \n",
       "4                            1                  0                  0   \n",
       "...                        ...                ...                ...   \n",
       "10343                        0                  0                  0   \n",
       "10344                        1                  0                  0   \n",
       "10345                        1                  0                  0   \n",
       "10346                        1                  0                  0   \n",
       "10347                        1                  0                  0   \n",
       "\n",
       "       FaturaSemPapel_No  FaturaSemPapel_Yes  \\\n",
       "0                      0                   1   \n",
       "1                      1                   0   \n",
       "2                      0                   1   \n",
       "3                      0                   1   \n",
       "4                      0                   1   \n",
       "...                  ...                 ...   \n",
       "10343                  0                   0   \n",
       "10344                  0                   1   \n",
       "10345                  0                   0   \n",
       "10346                  0                   0   \n",
       "10347                  1                   0   \n",
       "\n",
       "       FormaPagamento_Bank transfer (automatic)  \\\n",
       "0                                             0   \n",
       "1                                             0   \n",
       "2                                             0   \n",
       "3                                             0   \n",
       "4                                             0   \n",
       "...                                         ...   \n",
       "10343                                         0   \n",
       "10344                                         0   \n",
       "10345                                         0   \n",
       "10346                                         0   \n",
       "10347                                         0   \n",
       "\n",
       "       FormaPagamento_Credit card (automatic)  \\\n",
       "0                                           0   \n",
       "1                                           0   \n",
       "2                                           0   \n",
       "3                                           0   \n",
       "4                                           0   \n",
       "...                                       ...   \n",
       "10343                                       0   \n",
       "10344                                       0   \n",
       "10345                                       0   \n",
       "10346                                       0   \n",
       "10347                                       0   \n",
       "\n",
       "       FormaPagamento_Electronic check  FormaPagamento_Mailed check  \n",
       "0                                    0                            1  \n",
       "1                                    0                            1  \n",
       "2                                    1                            0  \n",
       "3                                    1                            0  \n",
       "4                                    0                            1  \n",
       "...                                ...                          ...  \n",
       "10343                                0                            0  \n",
       "10344                                0                            0  \n",
       "10345                                1                            0  \n",
       "10346                                1                            0  \n",
       "10347                                0                            0  \n",
       "\n",
       "[10348 rows x 48 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_balanced = pd.concat([y_resampled, x_resampled], axis = 1)\n",
    "data_balanced"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5174\n",
       "1    5174\n",
       "Name: ClienteCancelado, dtype: int64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_balanced.ClienteCancelado.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Existem 5174 clientes que tem contrato com a empresa e 5174 clientes que não possuem. Deste modo o dataset se encontra balanceado\n"
     ]
    }
   ],
   "source": [
    "print(f'Existem {data_balanced.ClienteCancelado.value_counts()[0]} clientes que tem contrato com a empresa e ' +\n",
    "      f'{data_balanced.ClienteCancelado.value_counts()[1]} clientes que não possuem. Deste modo o dataset se encontra balanceado')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Criar dois modelos de machine Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import ConfusionMatrixDisplay\n",
    "%matplotlib inline\n",
    "\n",
    "#Função para separação dos dados do dataset, em dados de treino e dados de teste\n",
    "def treino_teste(x, y):\n",
    "    x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.25, random_state = SEED)\n",
    "    return x_train, x_test, y_train, y_test    \n",
    "\n",
    "#Função para treinamento e previsão do modelo\n",
    "def classificador(classificador, x_train, x_test, y_train):\n",
    "    modelo = classificador.fit(x_train, y_train)\n",
    "    y_pred = modelo.predict(x_test)\n",
    "    return y_pred\n",
    "\n",
    "#Função para realizar metricas do modelo\n",
    "def metricas(y_pred, y_test):\n",
    "    print(\"Acurácia:\", round(metrics.accuracy_score(y_test, y_pred), 2))\n",
    "    print(\"Precisão:\", round(metrics.precision_score(y_test, y_pred), 2))\n",
    "    print(\"Recall:\", round(metrics.recall_score(y_test, y_pred), 2)) \n",
    "    print(\"F1:\", round(metrics.f1_score(y_test, y_pred), 2))\n",
    "    #print(\"Matriz de Confusão:\")\n",
    "    cm = confusion_matrix(y_test, y_pred)\n",
    "    disp = ConfusionMatrixDisplay(confusion_matrix = cm)\n",
    "    disp.plot()\n",
    "    \n",
    "#Curva Roc\n",
    "def curva(classificador, x_test, y_test):\n",
    "    y_pred_proba = classificador.predict_proba(x_test)[::, 1]\n",
    "    fpr, tpr, _ = metrics.roc_curve(y_test, y_pred_proba)\n",
    "    auc = metrics.roc_auc_score(y_test, y_pred_proba)\n",
    "    plt.rcParams['figure.figsize'] = (12., 8.)\n",
    "    plt.plot(fpr, tpr, label = 'LR, auc = ' + str(auc))\n",
    "    plt.plot([0,1], [0,1], color = 'red', lw = 2, linestyle = '--')\n",
    "    plt.legend(loc = 4)\n",
    "\n",
    "#Comparação de Metricas\n",
    "def comp_metricas(classificadores, x, y):\n",
    "    x_train, x_test, y_train, y_test = treino_teste(x, y)\n",
    "    for classifier in classificadores:\n",
    "        cf = classifier\n",
    "        y_pred = classificador(cf, x_train, x_test, y_train)\n",
    "        name = classifier.__class__.__name__\n",
    "        print(\"=\"*30)\n",
    "        print(name)\n",
    "        print('')\n",
    "        print('****Resultados****')\n",
    "        metricas(y_pred, y_test)\n",
    "        print('')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regressão Logística"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Dados x e y\n",
    "\n",
    "x = data_balanced.drop('ClienteCancelado', axis = 1)\n",
    "y = data_balanced['ClienteCancelado']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Separação de dados teste e treino\n",
    "x_train, x_test, y_train, y_test = treino_teste(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "#treino e previsão\n",
    "\n",
    "rl = LogisticRegression(max_iter = 1000, random_state = SEED)\n",
    "y_pred_rl = classificador(rl, x_train, x_test, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia: 0.86\n",
      "Precisão: 0.88\n",
      "Recall: 0.84\n",
      "F1: 0.86\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Metricas\n",
    "metricas(y_pred_rl, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "curva(rl, x_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia: 0.83\n",
      "Precisão: 0.8\n",
      "Recall: 0.89\n",
      "F1: 0.84\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rf = RandomForestClassifier(max_depth = 5, random_state = SEED)\n",
    "y_pred_rf = classificador(rf, x_train, x_test, y_train)\n",
    "metricas(y_pred_rf, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "curva(rf, x_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Árvore de Decisão"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia: 0.82\n",
      "Precisão: 0.78\n",
      "Recall: 0.88\n",
      "F1: 0.83\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt = DecisionTreeClassifier(max_depth = 5, random_state = SEED)\n",
    "y_pred_dt = classificador(dt, x_train, x_test, y_train)\n",
    "metricas(y_pred_dt, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "curva(dt, x_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Comparação das métricas dos modelos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "classificadores = [\n",
    "    LogisticRegression(max_iter = 1000, random_state = SEED),\n",
    "    RandomForestClassifier(max_depth = 5, random_state = SEED),\n",
    "    DecisionTreeClassifier(max_depth = 5, random_state = SEED)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==============================\n",
      "LogisticRegression\n",
      "\n",
      "****Resultados****\n",
      "Acurácia: 0.86\n",
      "Precisão: 0.88\n",
      "Recall: 0.84\n",
      "F1: 0.86\n",
      "\n",
      "==============================\n",
      "RandomForestClassifier\n",
      "\n",
      "****Resultados****\n",
      "Acurácia: 0.83\n",
      "Precisão: 0.8\n",
      "Recall: 0.89\n",
      "F1: 0.84\n",
      "\n",
      "==============================\n",
      "DecisionTreeClassifier\n",
      "\n",
      "****Resultados****\n",
      "Acurácia: 0.82\n",
      "Precisão: 0.78\n",
      "Recall: 0.88\n",
      "F1: 0.83\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "comp_metricas(classificadores, x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Melhorar Modelo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Como foi visto anteriormente, o recall do modelo que utiliza a Randon Forest obteve o a melhor metrica de recall. Essa que mede a proporção entre os Verdadeiros positivos, ou seja, a quantidade de resultados positivos o modelo acertou. Para melhorar o modelo será utilizada o método RandomizedSearchCV."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_estimators = np.arange(20, 1000, step = 20)\n",
    "criterion = ['gini', 'entropy']\n",
    "max_features = ['sqrt', 'log2']\n",
    "max_depth = list(np.arange(2, 1000, step = 1))\n",
    "min_samples_split = np.arange(2, 1000, step=2)\n",
    "min_samples_leaf = [1, 2, 4]\n",
    "bootstrap = [True, False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "param_grid = {\n",
    "    \"n_estimators\": n_estimators,\n",
    "    \"criterion\": criterion,\n",
    "    \"max_features\": max_features,\n",
    "    \"max_depth\": max_depth,\n",
    "    \"min_samples_split\": min_samples_split,\n",
    "    \"min_samples_leaf\": min_samples_leaf,\n",
    "    \"bootstrap\": bootstrap,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "\n",
    "rforest = RandomForestClassifier(random_state = SEED)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "random_cv = RandomizedSearchCV(rforest, param_grid, n_iter = 5, cv = 3, scoring = 'recall', n_jobs = -1, random_state = SEED)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 29.5 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rcv = random_cv.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "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>mean_fit_time</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>param_n_estimators</th>\n",
       "      <th>param_min_samples_split</th>\n",
       "      <th>param_min_samples_leaf</th>\n",
       "      <th>param_max_features</th>\n",
       "      <th>param_max_depth</th>\n",
       "      <th>param_criterion</th>\n",
       "      <th>param_bootstrap</th>\n",
       "      <th>params</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>std_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.994176</td>\n",
       "      <td>0.512370</td>\n",
       "      <td>0.906639</td>\n",
       "      <td>0.058769</td>\n",
       "      <td>760</td>\n",
       "      <td>536</td>\n",
       "      <td>2</td>\n",
       "      <td>log2</td>\n",
       "      <td>524</td>\n",
       "      <td>entropy</td>\n",
       "      <td>False</td>\n",
       "      <td>{'n_estimators': 760, 'min_samples_split': 536, 'min_samples_leaf': 2, 'max_features': 'log2', 'max_depth': 524, 'criterion': 'entropy', 'bootstrap': False}</td>\n",
       "      <td>0.494493</td>\n",
       "      <td>0.916473</td>\n",
       "      <td>0.926377</td>\n",
       "      <td>0.779114</td>\n",
       "      <td>0.201298</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.274983</td>\n",
       "      <td>0.021436</td>\n",
       "      <td>0.033636</td>\n",
       "      <td>0.005436</td>\n",
       "      <td>20</td>\n",
       "      <td>446</td>\n",
       "      <td>2</td>\n",
       "      <td>log2</td>\n",
       "      <td>414</td>\n",
       "      <td>gini</td>\n",
       "      <td>False</td>\n",
       "      <td>{'n_estimators': 20, 'min_samples_split': 446, 'min_samples_leaf': 2, 'max_features': 'log2', 'max_depth': 414, 'criterion': 'gini', 'bootstrap': False}</td>\n",
       "      <td>0.502029</td>\n",
       "      <td>0.909513</td>\n",
       "      <td>0.895072</td>\n",
       "      <td>0.768871</td>\n",
       "      <td>0.188778</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.701440</td>\n",
       "      <td>0.135677</td>\n",
       "      <td>0.675541</td>\n",
       "      <td>0.007182</td>\n",
       "      <td>720</td>\n",
       "      <td>736</td>\n",
       "      <td>2</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>846</td>\n",
       "      <td>gini</td>\n",
       "      <td>True</td>\n",
       "      <td>{'n_estimators': 720, 'min_samples_split': 736, 'min_samples_leaf': 2, 'max_features': 'sqrt', 'max_depth': 846, 'criterion': 'gini', 'bootstrap': True}</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.892111</td>\n",
       "      <td>0.884058</td>\n",
       "      <td>0.765390</td>\n",
       "      <td>0.173548</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.102881</td>\n",
       "      <td>1.006262</td>\n",
       "      <td>0.464242</td>\n",
       "      <td>0.116409</td>\n",
       "      <td>380</td>\n",
       "      <td>80</td>\n",
       "      <td>2</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>899</td>\n",
       "      <td>gini</td>\n",
       "      <td>False</td>\n",
       "      <td>{'n_estimators': 380, 'min_samples_split': 80, 'min_samples_leaf': 2, 'max_features': 'sqrt', 'max_depth': 899, 'criterion': 'gini', 'bootstrap': False}</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.958817</td>\n",
       "      <td>0.982609</td>\n",
       "      <td>0.780475</td>\n",
       "      <td>0.269212</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.601818</td>\n",
       "      <td>0.228693</td>\n",
       "      <td>0.111230</td>\n",
       "      <td>0.013465</td>\n",
       "      <td>120</td>\n",
       "      <td>732</td>\n",
       "      <td>2</td>\n",
       "      <td>sqrt</td>\n",
       "      <td>444</td>\n",
       "      <td>entropy</td>\n",
       "      <td>False</td>\n",
       "      <td>{'n_estimators': 120, 'min_samples_split': 732, 'min_samples_leaf': 2, 'max_features': 'sqrt', 'max_depth': 444, 'criterion': 'entropy', 'bootstrap': False}</td>\n",
       "      <td>0.496812</td>\n",
       "      <td>0.909513</td>\n",
       "      <td>0.910145</td>\n",
       "      <td>0.772156</td>\n",
       "      <td>0.194698</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_fit_time  std_fit_time  mean_score_time  std_score_time  \\\n",
       "0      10.994176      0.512370         0.906639        0.058769   \n",
       "1       0.274983      0.021436         0.033636        0.005436   \n",
       "2       7.701440      0.135677         0.675541        0.007182   \n",
       "3       7.102881      1.006262         0.464242        0.116409   \n",
       "4       1.601818      0.228693         0.111230        0.013465   \n",
       "\n",
       "  param_n_estimators param_min_samples_split param_min_samples_leaf  \\\n",
       "0                760                     536                      2   \n",
       "1                 20                     446                      2   \n",
       "2                720                     736                      2   \n",
       "3                380                      80                      2   \n",
       "4                120                     732                      2   \n",
       "\n",
       "  param_max_features param_max_depth param_criterion param_bootstrap  \\\n",
       "0               log2             524         entropy           False   \n",
       "1               log2             414            gini           False   \n",
       "2               sqrt             846            gini            True   \n",
       "3               sqrt             899            gini           False   \n",
       "4               sqrt             444         entropy           False   \n",
       "\n",
       "                                                                                                                                                         params  \\\n",
       "0  {'n_estimators': 760, 'min_samples_split': 536, 'min_samples_leaf': 2, 'max_features': 'log2', 'max_depth': 524, 'criterion': 'entropy', 'bootstrap': False}   \n",
       "1      {'n_estimators': 20, 'min_samples_split': 446, 'min_samples_leaf': 2, 'max_features': 'log2', 'max_depth': 414, 'criterion': 'gini', 'bootstrap': False}   \n",
       "2      {'n_estimators': 720, 'min_samples_split': 736, 'min_samples_leaf': 2, 'max_features': 'sqrt', 'max_depth': 846, 'criterion': 'gini', 'bootstrap': True}   \n",
       "3      {'n_estimators': 380, 'min_samples_split': 80, 'min_samples_leaf': 2, 'max_features': 'sqrt', 'max_depth': 899, 'criterion': 'gini', 'bootstrap': False}   \n",
       "4  {'n_estimators': 120, 'min_samples_split': 732, 'min_samples_leaf': 2, 'max_features': 'sqrt', 'max_depth': 444, 'criterion': 'entropy', 'bootstrap': False}   \n",
       "\n",
       "   split0_test_score  split1_test_score  split2_test_score  mean_test_score  \\\n",
       "0           0.494493           0.916473           0.926377         0.779114   \n",
       "1           0.502029           0.909513           0.895072         0.768871   \n",
       "2           0.520000           0.892111           0.884058         0.765390   \n",
       "3           0.400000           0.958817           0.982609         0.780475   \n",
       "4           0.496812           0.909513           0.910145         0.772156   \n",
       "\n",
       "   std_test_score  rank_test_score  \n",
       "0        0.201298                2  \n",
       "1        0.188778                4  \n",
       "2        0.173548                5  \n",
       "3        0.269212                1  \n",
       "4        0.194698                3  "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(rcv.cv_results_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'n_estimators': 380,\n",
       " 'min_samples_split': 80,\n",
       " 'min_samples_leaf': 2,\n",
       " 'max_features': 'sqrt',\n",
       " 'max_depth': 899,\n",
       " 'criterion': 'gini',\n",
       " 'bootstrap': False}"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rcv.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "rfn = RandomForestClassifier(**rcv.best_params_, random_state = SEED)\n",
    "\n",
    "model = rfn.fit(x_train, y_train)\n",
    "y_pred = rfn.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia: 0.86\n",
      "Precisão: 0.86\n",
      "Recall: 0.86\n",
      "F1: 0.86\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metricas(y_pred, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preciso revisar algumas informações....antes de continuar"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.12 ('base')",
   "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": "3.9.12"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "2d7e2abc49ad32e327445113e9255002ce2bfc2b3818d1bb0173a7df173d287f"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}