Demo_of_AutoGluon.ipynb

{
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  "metadata": {
    "colab": {
      "name": "Demo of AutoGluon.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/srivatsan88/YouTubeLI/blob/master/Demo_of_AutoGluon.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ydtu2LgJT7RP",
        "colab_type": "text"
      },
      "source": [
        "This notebook purpose is to try out AutoGluon package open sourced by AWS. The project details is available in link below\n",
        "\n",
        "https://autogluon.mxnet.io/\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kbHRfwu_CTJP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!pip install --upgrade mxnet\n",
        "!pip install autogluon"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8ZZN307DAnqn",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import autogluon as ag\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import os,urllib"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v8wG9E2WFnL7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from autogluon import TabularPrediction as task"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "x4hcBdZS3GfD",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "BASE_DIR = '/tmp'\n",
        "OUTPUT_FILE = os.path.join(BASE_DIR, 'churn_data.csv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DQTBl8AV3kZi",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "churn_data=urllib.request.urlretrieve('https://raw.githubusercontent.com/srivatsan88/YouTubeLI/master/dataset/WA_Fn-UseC_-Telco-Customer-Churn.csv', OUTPUT_FILE)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DPZBGNP-3nOe",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "churn_master_df = pd.read_csv(OUTPUT_FILE)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hVS5AOoh3sOj",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "size = int(0.8*churn_master_df.shape[0])\n",
        "train_df = churn_master_df[:size]\n",
        "test_df = churn_master_df[size:]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cFvuBVYrPhHB",
        "colab_type": "code",
        "outputId": "0ad4db4e-9ebc-49d8-f3c5-8d176f9deaff",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "test_df.shape"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1409, 21)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7PWUHr19M1e1",
        "colab_type": "code",
        "outputId": "011820f1-f6a7-4c1d-cc3b-3ebf66672478",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "test_df"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .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>customerID</th>\n",
              "      <th>gender</th>\n",
              "      <th>SeniorCitizen</th>\n",
              "      <th>Partner</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>tenure</th>\n",
              "      <th>PhoneService</th>\n",
              "      <th>MultipleLines</th>\n",
              "      <th>InternetService</th>\n",
              "      <th>OnlineSecurity</th>\n",
              "      <th>OnlineBackup</th>\n",
              "      <th>DeviceProtection</th>\n",
              "      <th>TechSupport</th>\n",
              "      <th>StreamingTV</th>\n",
              "      <th>StreamingMovies</th>\n",
              "      <th>Contract</th>\n",
              "      <th>PaperlessBilling</th>\n",
              "      <th>PaymentMethod</th>\n",
              "      <th>MonthlyCharges</th>\n",
              "      <th>TotalCharges</th>\n",
              "      <th>Churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>5634</th>\n",
              "      <td>2320-JRSDE</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>19.90</td>\n",
              "      <td>19.9</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5635</th>\n",
              "      <td>2087-QAREY</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>22</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>54.70</td>\n",
              "      <td>1178.75</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5636</th>\n",
              "      <td>0601-WZHJF</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>14</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>No</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>46.35</td>\n",
              "      <td>667.7</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5637</th>\n",
              "      <td>4423-JWZJN</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>64</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</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>Yes</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>90.25</td>\n",
              "      <td>5629.15</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5638</th>\n",
              "      <td>5143-WMWOG</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>No</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>19.95</td>\n",
              "      <td>19.95</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5639</th>\n",
              "      <td>6490-FGZAT</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>6</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>20.65</td>\n",
              "      <td>109.3</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5640</th>\n",
              "      <td>5393-RXQSZ</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</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>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>No</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>79.60</td>\n",
              "      <td>79.6</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5641</th>\n",
              "      <td>7452-FOLON</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>39</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>25.45</td>\n",
              "      <td>958.45</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5642</th>\n",
              "      <td>2320-TZRRH</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>20</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>19.50</td>\n",
              "      <td>403.15</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5643</th>\n",
              "      <td>0231-LXVAP</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</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>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>75.90</td>\n",
              "      <td>75.9</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5644</th>\n",
              "      <td>9444-JTXHZ</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>1</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>No</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>76.20</td>\n",
              "      <td>76.2</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5645</th>\n",
              "      <td>4942-VZZOM</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>64</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>66.15</td>\n",
              "      <td>4392.5</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5646</th>\n",
              "      <td>5510-BOIUJ</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>19.25</td>\n",
              "      <td>19.25</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5647</th>\n",
              "      <td>7502-BNYGS</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>46</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>No</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>69.10</td>\n",
              "      <td>3168</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5648</th>\n",
              "      <td>4291-HYEBC</td>\n",
              "      <td>Female</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>28</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>39.10</td>\n",
              "      <td>1096.6</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5649</th>\n",
              "      <td>6147-CBCRA</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>33</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>20.05</td>\n",
              "      <td>669.45</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5650</th>\n",
              "      <td>6047-SUHPR</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>39</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>59.80</td>\n",
              "      <td>2343.85</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5651</th>\n",
              "      <td>4471-KXAUH</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>42</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</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>84.30</td>\n",
              "      <td>3588.4</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5652</th>\n",
              "      <td>9752-ZNQUT</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</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>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>48.60</td>\n",
              "      <td>48.6</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5653</th>\n",
              "      <td>7638-QVMVY</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>7</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>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>79.00</td>\n",
              "      <td>522.95</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5654</th>\n",
              "      <td>1576-PFZIW</td>\n",
              "      <td>Male</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>70</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>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Two year</td>\n",
              "      <td>No</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>105.35</td>\n",
              "      <td>7511.9</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5655</th>\n",
              "      <td>5666-MBJPT</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>65</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Two year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>25.10</td>\n",
              "      <td>1725</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5656</th>\n",
              "      <td>7312-XSBAT</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</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>No</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>49.75</td>\n",
              "      <td>49.75</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5657</th>\n",
              "      <td>3096-GKWEB</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>18</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>94.75</td>\n",
              "      <td>1691.9</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5658</th>\n",
              "      <td>2371-JQHZZ</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>24</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>93.00</td>\n",
              "      <td>2248.05</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5659</th>\n",
              "      <td>0674-GCDXG</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>63</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Two year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>71.90</td>\n",
              "      <td>4479.2</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5660</th>\n",
              "      <td>1121-QSIVB</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>44</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>77.55</td>\n",
              "      <td>3471.1</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5661</th>\n",
              "      <td>4396-KLSEH</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>4</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>19.85</td>\n",
              "      <td>63</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5662</th>\n",
              "      <td>3244-DCJWY</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</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>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>70.25</td>\n",
              "      <td>70.25</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5663</th>\n",
              "      <td>2824-MYYBN</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>37</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>95.25</td>\n",
              "      <td>3314.15</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7013</th>\n",
              "      <td>1685-BQULA</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>40</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>93.40</td>\n",
              "      <td>3756.4</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7014</th>\n",
              "      <td>9053-EJUNL</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>41</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>89.20</td>\n",
              "      <td>3645.75</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7015</th>\n",
              "      <td>0666-UXTJO</td>\n",
              "      <td>Male</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>34</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>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>85.20</td>\n",
              "      <td>2874.45</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7016</th>\n",
              "      <td>1471-GIQKQ</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</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>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>No</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>49.95</td>\n",
              "      <td>49.95</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7017</th>\n",
              "      <td>4807-IZYOZ</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>51</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Two year</td>\n",
              "      <td>No</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>20.65</td>\n",
              "      <td>1020.75</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7018</th>\n",
              "      <td>1122-JWTJW</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1</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>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>70.65</td>\n",
              "      <td>70.65</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7019</th>\n",
              "      <td>9710-NJERN</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>39</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Two year</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>20.15</td>\n",
              "      <td>826</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7020</th>\n",
              "      <td>9837-FWLCH</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>12</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>19.20</td>\n",
              "      <td>239</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7021</th>\n",
              "      <td>1699-HPSBG</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>12</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>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>59.80</td>\n",
              "      <td>727.8</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7022</th>\n",
              "      <td>7203-OYKCT</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>72</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>104.95</td>\n",
              "      <td>7544.3</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7023</th>\n",
              "      <td>1035-IPQPU</td>\n",
              "      <td>Female</td>\n",
              "      <td>1</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>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>103.50</td>\n",
              "      <td>6479.4</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7024</th>\n",
              "      <td>7398-LXGYX</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>44</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>84.80</td>\n",
              "      <td>3626.35</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7025</th>\n",
              "      <td>2823-LKABH</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>18</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>95.05</td>\n",
              "      <td>1679.4</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7026</th>\n",
              "      <td>8775-CEBBJ</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</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>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>44.20</td>\n",
              "      <td>403.35</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7027</th>\n",
              "      <td>0550-DCXLH</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>13</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>Yes</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>No</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>73.35</td>\n",
              "      <td>931.55</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7028</th>\n",
              "      <td>9281-CEDRU</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>68</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>Two year</td>\n",
              "      <td>No</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>64.10</td>\n",
              "      <td>4326.25</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7029</th>\n",
              "      <td>2235-DWLJU</td>\n",
              "      <td>Female</td>\n",
              "      <td>1</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>6</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</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>44.40</td>\n",
              "      <td>263.05</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7030</th>\n",
              "      <td>0871-OPBXW</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>20.05</td>\n",
              "      <td>39.25</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7031</th>\n",
              "      <td>3605-JISKB</td>\n",
              "      <td>Male</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>55</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>60.00</td>\n",
              "      <td>3316.1</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7032</th>\n",
              "      <td>6894-LFHLY</td>\n",
              "      <td>Male</td>\n",
              "      <td>1</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>75.75</td>\n",
              "      <td>75.75</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7033</th>\n",
              "      <td>9767-FFLEM</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>38</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>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>69.50</td>\n",
              "      <td>2625.25</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7034</th>\n",
              "      <td>0639-TSIQW</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>67</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>102.95</td>\n",
              "      <td>6886.25</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7035</th>\n",
              "      <td>8456-QDAVC</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>19</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>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>78.70</td>\n",
              "      <td>1495.1</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7036</th>\n",
              "      <td>7750-EYXWZ</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>12</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>One year</td>\n",
              "      <td>No</td>\n",
              "      <td>Electronic check</td>\n",
              "      <td>60.65</td>\n",
              "      <td>743.3</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7037</th>\n",
              "      <td>2569-WGERO</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>72</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>No internet service</td>\n",
              "      <td>Two year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Bank transfer (automatic)</td>\n",
              "      <td>21.15</td>\n",
              "      <td>1419.4</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7038</th>\n",
              "      <td>6840-RESVB</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>24</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>84.80</td>\n",
              "      <td>1990.5</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7039</th>\n",
              "      <td>2234-XADUH</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>72</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>One year</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Credit card (automatic)</td>\n",
              "      <td>103.20</td>\n",
              "      <td>7362.9</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7040</th>\n",
              "      <td>4801-JZAZL</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>11</td>\n",
              "      <td>No</td>\n",
              "      <td>No phone service</td>\n",
              "      <td>DSL</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>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>29.60</td>\n",
              "      <td>346.45</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7041</th>\n",
              "      <td>8361-LTMKD</td>\n",
              "      <td>Male</td>\n",
              "      <td>1</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>4</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Month-to-month</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Mailed check</td>\n",
              "      <td>74.40</td>\n",
              "      <td>306.6</td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7042</th>\n",
              "      <td>3186-AJIEK</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>66</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Fiber optic</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</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>105.65</td>\n",
              "      <td>6844.5</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1409 rows × 21 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      customerID  gender  SeniorCitizen  ... MonthlyCharges TotalCharges  Churn\n",
              "5634  2320-JRSDE  Female              0  ...          19.90         19.9    Yes\n",
              "5635  2087-QAREY  Female              0  ...          54.70      1178.75     No\n",
              "5636  0601-WZHJF    Male              0  ...          46.35        667.7    Yes\n",
              "5637  4423-JWZJN    Male              0  ...          90.25      5629.15     No\n",
              "5638  5143-WMWOG    Male              0  ...          19.95        19.95    Yes\n",
              "5639  6490-FGZAT    Male              0  ...          20.65        109.3     No\n",
              "5640  5393-RXQSZ    Male              0  ...          79.60         79.6    Yes\n",
              "5641  7452-FOLON    Male              0  ...          25.45       958.45     No\n",
              "5642  2320-TZRRH  Female              0  ...          19.50       403.15     No\n",
              "5643  0231-LXVAP    Male              0  ...          75.90         75.9    Yes\n",
              "5644  9444-JTXHZ    Male              0  ...          76.20         76.2    Yes\n",
              "5645  4942-VZZOM    Male              0  ...          66.15       4392.5     No\n",
              "5646  5510-BOIUJ    Male              0  ...          19.25        19.25    Yes\n",
              "5647  7502-BNYGS  Female              0  ...          69.10         3168     No\n",
              "5648  4291-HYEBC  Female              1  ...          39.10       1096.6     No\n",
              "5649  6147-CBCRA  Female              0  ...          20.05       669.45     No\n",
              "5650  6047-SUHPR    Male              0  ...          59.80      2343.85     No\n",
              "5651  4471-KXAUH  Female              0  ...          84.30       3588.4    Yes\n",
              "5652  9752-ZNQUT  Female              0  ...          48.60         48.6     No\n",
              "5653  7638-QVMVY  Female              0  ...          79.00       522.95    Yes\n",
              "5654  1576-PFZIW    Male              1  ...         105.35       7511.9     No\n",
              "5655  5666-MBJPT    Male              0  ...          25.10         1725     No\n",
              "5656  7312-XSBAT    Male              0  ...          49.75        49.75     No\n",
              "5657  3096-GKWEB    Male              0  ...          94.75       1691.9     No\n",
              "5658  2371-JQHZZ    Male              0  ...          93.00      2248.05     No\n",
              "5659  0674-GCDXG    Male              0  ...          71.90       4479.2     No\n",
              "5660  1121-QSIVB  Female              0  ...          77.55       3471.1     No\n",
              "5661  4396-KLSEH    Male              0  ...          19.85           63     No\n",
              "5662  3244-DCJWY  Female              0  ...          70.25        70.25    Yes\n",
              "5663  2824-MYYBN  Female              0  ...          95.25      3314.15     No\n",
              "...          ...     ...            ...  ...            ...          ...    ...\n",
              "7013  1685-BQULA  Female              0  ...          93.40       3756.4     No\n",
              "7014  9053-EJUNL    Male              0  ...          89.20      3645.75     No\n",
              "7015  0666-UXTJO    Male              1  ...          85.20      2874.45     No\n",
              "7016  1471-GIQKQ  Female              0  ...          49.95        49.95     No\n",
              "7017  4807-IZYOZ  Female              0  ...          20.65      1020.75     No\n",
              "7018  1122-JWTJW    Male              0  ...          70.65        70.65    Yes\n",
              "7019  9710-NJERN  Female              0  ...          20.15          826     No\n",
              "7020  9837-FWLCH    Male              0  ...          19.20          239     No\n",
              "7021  1699-HPSBG    Male              0  ...          59.80        727.8    Yes\n",
              "7022  7203-OYKCT    Male              0  ...         104.95       7544.3     No\n",
              "7023  1035-IPQPU  Female              1  ...         103.50       6479.4     No\n",
              "7024  7398-LXGYX    Male              0  ...          84.80      3626.35     No\n",
              "7025  2823-LKABH  Female              0  ...          95.05       1679.4     No\n",
              "7026  8775-CEBBJ  Female              0  ...          44.20       403.35    Yes\n",
              "7027  0550-DCXLH    Male              0  ...          73.35       931.55     No\n",
              "7028  9281-CEDRU  Female              0  ...          64.10      4326.25     No\n",
              "7029  2235-DWLJU  Female              1  ...          44.40       263.05     No\n",
              "7030  0871-OPBXW  Female              0  ...          20.05        39.25     No\n",
              "7031  3605-JISKB    Male              1  ...          60.00       3316.1     No\n",
              "7032  6894-LFHLY    Male              1  ...          75.75        75.75    Yes\n",
              "7033  9767-FFLEM    Male              0  ...          69.50      2625.25     No\n",
              "7034  0639-TSIQW  Female              0  ...         102.95      6886.25    Yes\n",
              "7035  8456-QDAVC    Male              0  ...          78.70       1495.1     No\n",
              "7036  7750-EYXWZ  Female              0  ...          60.65        743.3     No\n",
              "7037  2569-WGERO  Female              0  ...          21.15       1419.4     No\n",
              "7038  6840-RESVB    Male              0  ...          84.80       1990.5     No\n",
              "7039  2234-XADUH  Female              0  ...         103.20       7362.9     No\n",
              "7040  4801-JZAZL  Female              0  ...          29.60       346.45     No\n",
              "7041  8361-LTMKD    Male              1  ...          74.40        306.6    Yes\n",
              "7042  3186-AJIEK    Male              0  ...         105.65       6844.5     No\n",
              "\n",
              "[1409 rows x 21 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WkSKEXkSODD_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "train_data = task.Dataset(df=train_df)\n",
        "test_data = task.Dataset(df=test_df)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "doezfFcKOKBD",
        "colab_type": "code",
        "outputId": "6501ec3f-f748-4d82-9346-a3447821f6a8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 158
        }
      },
      "source": [
        "print(train_data.head())"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "   customerID  gender  SeniorCitizen  ... MonthlyCharges TotalCharges  Churn\n",
            "0  7590-VHVEG  Female              0  ...          29.85        29.85     No\n",
            "1  5575-GNVDE    Male              0  ...          56.95       1889.5     No\n",
            "2  3668-QPYBK    Male              0  ...          53.85       108.15    Yes\n",
            "3  7795-CFOCW    Male              0  ...          42.30      1840.75     No\n",
            "4  9237-HQITU  Female              0  ...          70.70       151.65    Yes\n",
            "\n",
            "[5 rows x 21 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l9_irMW5OVYb",
        "colab_type": "code",
        "outputId": "d0034fb4-1918-40ce-fbe7-6b48da6bec20",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 176
        }
      },
      "source": [
        "print(test_data.describe())"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "       SeniorCitizen       tenure  MonthlyCharges\n",
            "count    1409.000000  1409.000000     1409.000000\n",
            "mean        0.168914    32.669269       64.338680\n",
            "std         0.374809    24.449128       30.058771\n",
            "min         0.000000     0.000000       18.550000\n",
            "25%         0.000000     9.000000       35.300000\n",
            "50%         0.000000    30.000000       70.100000\n",
            "75%         0.000000    56.000000       89.650000\n",
            "max         1.000000    72.000000      118.200000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NEf2bpXRRc8B",
        "colab_type": "code",
        "outputId": "ec311969-4ddf-4203-98fb-e26eab2062ac",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 105
        }
      },
      "source": [
        "label_column = 'Churn'\n",
        "train_data[label_column].describe()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count     5634\n",
              "unique       2\n",
              "top         No\n",
              "freq      4146\n",
              "Name: Churn, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "20hS8cclOG1_",
        "colab_type": "code",
        "outputId": "899b7ede-e507-43e4-c4f6-c82bbd8973e3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 834
        }
      },
      "source": [
        "predictor = task.fit(train_data=train_data, label=label_column, eval_metric='accuracy')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "No output_directory specified. Models will be saved in: AutogluonModels/ag-20200201_133255/\n",
            "Beginning AutoGluon training ...\n",
            "AutoGluon will save models to AutogluonModels/ag-20200201_133255/\n",
            "Preprocessing data ...\n",
            "Here are the first 10 unique label values in your data:  ['No' 'Yes']\n",
            "AutoGluon infers your prediction problem is: binary  (because only two unique label-values observed)\n",
            "If this is wrong, please specify `problem_type` argument in fit() instead (You may specify problem_type as one of: ['binary', 'multiclass', 'regression'])\n",
            "\n",
            "Selected class <--> label mapping:  class 1 = Yes, class 0 = No\n",
            "\tData preprocessing and feature engineering runtime = 0.15s ...\n",
            "AutoGluon will gauge predictive performance using evaluation metric: accuracy\n",
            "To change this, specify the eval_metric argument of fit()\n",
            "Fitting model: RandomForestClassifierGini ...\n",
            "\t1.62s\t = Training runtime\n",
            "\t0.7695\t = Validation accuracy score\n",
            "Fitting model: RandomForestClassifierEntr ...\n",
            "\t1.92s\t = Training runtime\n",
            "\t0.7855\t = Validation accuracy score\n",
            "Fitting model: ExtraTreesClassifierGini ...\n",
            "\t1.21s\t = Training runtime\n",
            "\t0.7677\t = Validation accuracy score\n",
            "Fitting model: ExtraTreesClassifierEntr ...\n",
            "\t1.43s\t = Training runtime\n",
            "\t0.766\t = Validation accuracy score\n",
            "Fitting model: KNeighborsClassifierUnif ...\n",
            "\t0.01s\t = Training runtime\n",
            "\t0.773\t = Validation accuracy score\n",
            "Fitting model: KNeighborsClassifierDist ...\n",
            "\t0.02s\t = Training runtime\n",
            "\t0.7411\t = Validation accuracy score\n",
            "Fitting model: LightGBMClassifier ...\n",
            "\t0.65s\t = Training runtime\n",
            "\t0.789\t = Validation accuracy score\n",
            "Fitting model: CatboostClassifier ...\n",
            "\t3.36s\t = Training runtime\n",
            "\t0.7996\t = Validation accuracy score\n",
            "Fitting model: NeuralNetClassifier ...\n",
            "\t23.89s\t = Training runtime\n",
            "\t0.7766\t = Validation accuracy score\n",
            "Fitting model: LightGBMClassifierCustom ...\n",
            "\t0.98s\t = Training runtime\n",
            "\t0.7784\t = Validation accuracy score\n",
            "Fitting model: weighted_ensemble_k0_l1 ...\n",
            "\t0.56s\t = Training runtime\n",
            "\t0.805\t = Validation accuracy score\n",
            "AutoGluon training complete, total runtime = 39.04s ...\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RKJQjEjlSciM",
        "colab_type": "code",
        "outputId": "bf4574ed-ad27-4661-9c3f-a8757a2e062e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 158
        }
      },
      "source": [
        "y_test = test_data[label_column]\n",
        "\n",
        "test_data_nolab = test_data.drop(labels=[label_column],axis=1) \n",
        "print(test_data_nolab.head())\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "      customerID  gender  ...  MonthlyCharges TotalCharges\n",
            "5634  2320-JRSDE  Female  ...           19.90         19.9\n",
            "5635  2087-QAREY  Female  ...           54.70      1178.75\n",
            "5636  0601-WZHJF    Male  ...           46.35        667.7\n",
            "5637  4423-JWZJN    Male  ...           90.25      5629.15\n",
            "5638  5143-WMWOG    Male  ...           19.95        19.95\n",
            "\n",
            "[5 rows x 20 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VzuKEScsTO8_",
        "colab_type": "code",
        "outputId": "0290a3fb-7261-4e27-d009-02510bc1d9ef",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 692
        }
      },
      "source": [
        "y_pred = predictor.predict(test_data_nolab)\n",
        "print(\"Predictions:  \", y_pred)\n",
        "perf = predictor.evaluate_predictions(y_true=y_test, y_pred=y_pred, auxiliary_metrics=True)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Evaluation: accuracy on test data: 0.804116\n",
            "Evaluations on test data:\n",
            "{\n",
            "    \"accuracy\": 0.8041163946061036,\n",
            "    \"accuracy_score\": 0.8041163946061036,\n",
            "    \"balanced_accuracy_score\": 0.7129571473799239,\n",
            "    \"matthews_corrcoef\": 0.46972522668426253,\n",
            "    \"f1_score\": 0.8041163946061036\n",
            "}\n",
            "Detailed (per-class) classification report:\n",
            "{\n",
            "    \"No\": {\n",
            "        \"precision\": 0.8351158645276292,\n",
            "        \"recall\": 0.9114785992217899,\n",
            "        \"f1-score\": 0.8716279069767442,\n",
            "        \"support\": 1028\n",
            "    },\n",
            "    \"Yes\": {\n",
            "        \"precision\": 0.6829268292682927,\n",
            "        \"recall\": 0.5144356955380578,\n",
            "        \"f1-score\": 0.5868263473053893,\n",
            "        \"support\": 381\n",
            "    },\n",
            "    \"accuracy\": 0.8041163946061036,\n",
            "    \"macro avg\": {\n",
            "        \"precision\": 0.759021346897961,\n",
            "        \"recall\": 0.7129571473799239,\n",
            "        \"f1-score\": 0.7292271271410667,\n",
            "        \"support\": 1409\n",
            "    },\n",
            "    \"weighted avg\": {\n",
            "        \"precision\": 0.7939632581161267,\n",
            "        \"recall\": 0.8041163946061036,\n",
            "        \"f1-score\": 0.7946162716078399,\n",
            "        \"support\": 1409\n",
            "    }\n",
            "}\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Predictions:   ['No' 'No' 'No' ... 'No' 'Yes' 'No']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GMf8KwNXU1Qz",
        "colab_type": "code",
        "outputId": "eea2bebf-9daa-4036-c187-a7c61163118a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "print(predictor.problem_type)\n",
        "print(predictor.feature_types)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "binary\n",
            "{'nlp': [], 'vectorizers': [], 'object': ['customerID', 'gender', 'Partner', 'Dependents', 'PhoneService', 'MultipleLines', 'InternetService', 'OnlineSecurity', 'OnlineBackup', 'DeviceProtection', 'TechSupport', 'StreamingTV', 'StreamingMovies', 'Contract', 'PaperlessBilling', 'PaymentMethod', 'TotalCharges'], 'int': ['SeniorCitizen', 'tenure'], 'float': ['MonthlyCharges']}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uZRuPA2oU8oH",
        "colab_type": "code",
        "outputId": "5ca13ce4-90df-430f-f91a-256867bd3ac2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "predictor.predict_proba(test_data_nolab)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.33869589, 0.26914778, 0.38509076, ..., 0.34786474, 0.68145563,\n",
              "       0.1184664 ])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gY8DpwIvHdVA",
        "colab_type": "code",
        "outputId": "bbc7050c-3c65-4a6b-c996-d5ba0436c06f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        }
      },
      "source": [
        "predictor.leaderboard()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                         model  score_val   fit_time  pred_time_val  stack_level\n",
            "10     weighted_ensemble_k0_l1   0.804965   0.557642       0.001467            1\n",
            "7           CatboostClassifier   0.799645   3.355235       0.025838            0\n",
            "6           LightGBMClassifier   0.789007   0.652690       0.018786            0\n",
            "1   RandomForestClassifierEntr   0.785461   1.915805       0.115646            0\n",
            "9     LightGBMClassifierCustom   0.778369   0.981799       0.020075            0\n",
            "8          NeuralNetClassifier   0.776596  23.890445       0.232876            0\n",
            "4     KNeighborsClassifierUnif   0.773050   0.012174       0.109095            0\n",
            "0   RandomForestClassifierGini   0.769504   1.619533       0.116632            0\n",
            "2     ExtraTreesClassifierGini   0.767730   1.211062       0.116087            0\n",
            "3     ExtraTreesClassifierEntr   0.765957   1.425109       0.119264            0\n",
            "5     KNeighborsClassifierDist   0.741135   0.016396       0.107469            0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "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>model</th>\n",
              "      <th>score_val</th>\n",
              "      <th>fit_time</th>\n",
              "      <th>pred_time_val</th>\n",
              "      <th>stack_level</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>weighted_ensemble_k0_l1</td>\n",
              "      <td>0.804965</td>\n",
              "      <td>0.557642</td>\n",
              "      <td>0.001467</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>CatboostClassifier</td>\n",
              "      <td>0.799645</td>\n",
              "      <td>3.355235</td>\n",
              "      <td>0.025838</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>LightGBMClassifier</td>\n",
              "      <td>0.789007</td>\n",
              "      <td>0.652690</td>\n",
              "      <td>0.018786</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>RandomForestClassifierEntr</td>\n",
              "      <td>0.785461</td>\n",
              "      <td>1.915805</td>\n",
              "      <td>0.115646</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>LightGBMClassifierCustom</td>\n",
              "      <td>0.778369</td>\n",
              "      <td>0.981799</td>\n",
              "      <td>0.020075</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>NeuralNetClassifier</td>\n",
              "      <td>0.776596</td>\n",
              "      <td>23.890445</td>\n",
              "      <td>0.232876</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>KNeighborsClassifierUnif</td>\n",
              "      <td>0.773050</td>\n",
              "      <td>0.012174</td>\n",
              "      <td>0.109095</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>RandomForestClassifierGini</td>\n",
              "      <td>0.769504</td>\n",
              "      <td>1.619533</td>\n",
              "      <td>0.116632</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ExtraTreesClassifierGini</td>\n",
              "      <td>0.767730</td>\n",
              "      <td>1.211062</td>\n",
              "      <td>0.116087</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ExtraTreesClassifierEntr</td>\n",
              "      <td>0.765957</td>\n",
              "      <td>1.425109</td>\n",
              "      <td>0.119264</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>KNeighborsClassifierDist</td>\n",
              "      <td>0.741135</td>\n",
              "      <td>0.016396</td>\n",
              "      <td>0.107469</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                         model  score_val  ...  pred_time_val  stack_level\n",
              "10     weighted_ensemble_k0_l1   0.804965  ...       0.001467            1\n",
              "7           CatboostClassifier   0.799645  ...       0.025838            0\n",
              "6           LightGBMClassifier   0.789007  ...       0.018786            0\n",
              "1   RandomForestClassifierEntr   0.785461  ...       0.115646            0\n",
              "9     LightGBMClassifierCustom   0.778369  ...       0.020075            0\n",
              "8          NeuralNetClassifier   0.776596  ...       0.232876            0\n",
              "4     KNeighborsClassifierUnif   0.773050  ...       0.109095            0\n",
              "0   RandomForestClassifierGini   0.769504  ...       0.116632            0\n",
              "2     ExtraTreesClassifierGini   0.767730  ...       0.116087            0\n",
              "3     ExtraTreesClassifierEntr   0.765957  ...       0.119264            0\n",
              "5     KNeighborsClassifierDist   0.741135  ...       0.107469            0\n",
              "\n",
              "[11 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EMMqZG2cQbHk",
        "colab_type": "code",
        "outputId": "6c202d45-b9b5-4dbd-86df-67cf87f43ffa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 496
        }
      },
      "source": [
        "hp_tune = True \n",
        "\n",
        "rf_options = { \n",
        "    'n_estimators': 100, \n",
        "}\n",
        "\n",
        "gbm_options = { \n",
        "    'num_boost_round': 100, \n",
        "    'num_leaves': ag.space.Int(lower=6, upper=20, default=8), \n",
        "}\n",
        "\n",
        "hyperparameters = {'RF':rf_options, 'GBM': gbm_options}  \n",
        "\n",
        "time_limits = 2*60  \n",
        "num_trials = 1  \n",
        "search_strategy = 'skopt'  \n",
        "\n",
        "predictor = task.fit(train_data=train_data, tuning_data=test_data, label=label_column,\n",
        "                     time_limits=time_limits, num_trials=num_trials,\n",
        "                     hyperparameter_tune=hp_tune, hyperparameters=hyperparameters,\n",
        "                     search_strategy=search_strategy, nthreads_per_trial=1, ngpus_per_trial=1)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "No output_directory specified. Models will be saved in: AutogluonModels/ag-20200201_140350/\n",
            "Warning: Specified num_trials == 1 or time_limits is too small for hyperparameter_tune, setting to False.\n",
            "Beginning AutoGluon training ... Time limit = 120s\n",
            "AutoGluon will save models to AutogluonModels/ag-20200201_140350/\n",
            "Preprocessing data ...\n",
            "Here are the first 10 unique label values in your data:  ['No' 'Yes']\n",
            "AutoGluon infers your prediction problem is: binary  (because only two unique label-values observed)\n",
            "If this is wrong, please specify `problem_type` argument in fit() instead (You may specify problem_type as one of: ['binary', 'multiclass', 'regression'])\n",
            "\n",
            "Selected class <--> label mapping:  class 1 = Yes, class 0 = No\n",
            "\tData preprocessing and feature engineering runtime = 0.17s ...\n",
            "AutoGluon will gauge predictive performance using evaluation metric: accuracy\n",
            "To change this, specify the eval_metric argument of fit()\n",
            "Fitting model: RandomForestClassifierGini ... Training model for up to 119.83s of the 119.83s of remaining time.\n",
            "\t0.65s\t = Training runtime\n",
            "\t0.7949\t = Validation accuracy score\n",
            "Fitting model: RandomForestClassifierEntr ... Training model for up to 119.01s of the 119.01s of remaining time.\n",
            "\t0.77s\t = Training runtime\n",
            "\t0.8006\t = Validation accuracy score\n",
            "Fitting model: LightGBMClassifier ... Training model for up to 118.09s of the 118.09s of remaining time.\n",
            "Attempting to fit model without HPO, but search space is provided. fit() will only consider default hyperparameter values from search space.\n",
            "\t0.45s\t = Training runtime\n",
            "\t0.8027\t = Validation accuracy score\n",
            "Fitting model: weighted_ensemble_k0_l1 ...\n",
            "\t0.25s\t = Training runtime\n",
            "\t0.8091\t = Validation accuracy score\n",
            "AutoGluon training complete, total runtime = 2.95s ...\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GIg0uPpf98G0",
        "colab_type": "code",
        "outputId": "dbf7dfd8-719b-41d2-bf06-64c1d036f39c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "predictor.fit_summary()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "*** Summary of fit() ***\n",
            "Number of models trained: 4\n",
            "Types of models trained: \n",
            "{'WeightedEnsembleModel', 'LGBModel', 'RFModel'}\n",
            "Validation performance of individual models: {'RandomForestClassifierGini': 0.8026969481902059, 'RandomForestClassifierEntr': 0.8005677785663591, 'LightGBMClassifier': 0.8026969481902059, 'weighted_ensemble_k0_l1': 0.8090844570617459}\n",
            "Best model (based on validation performance): weighted_ensemble_k0_l1\n",
            "Hyperparameter-tuning used: False\n",
            "Bagging used: False \n",
            "Stack-ensembling used: False \n",
            "User-specified hyperparameters:\n",
            "{'RF': {'n_estimators': 100}, 'GBM': {'num_boost_round': 100, 'num_leaves': Int: lower=6, upper=20}}\n",
            "Plot summary of models saved to file: SummaryOfModels.html\n",
            "*** End of fit() summary ***\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'feature_prune': False,\n",
              " 'hyperparameter_tune': False,\n",
              " 'hyperparameters_userspecified': {'GBM': {'num_boost_round': 100,\n",
              "   'num_leaves': Int: lower=6, upper=20},\n",
              "  'RF': {'n_estimators': 100}},\n",
              " 'model_best': 'weighted_ensemble_k0_l1',\n",
              " 'model_fit_times': {'LightGBMClassifier': 0.44521427154541016,\n",
              "  'RandomForestClassifierEntr': 0.7557253837585449,\n",
              "  'RandomForestClassifierGini': 0.6558413505554199,\n",
              "  'weighted_ensemble_k0_l1': 0.26418185234069824},\n",
              " 'model_hyperparams': {'LightGBMClassifier': {'boosting_type': 'gbdt',\n",
              "   'metric': 'binary_logloss,binary_error',\n",
              "   'num_boost_round': 100,\n",
              "   'num_leaves': Int: lower=6, upper=20,\n",
              "   'num_threads': -1,\n",
              "   'objective': 'binary',\n",
              "   'two_round': True,\n",
              "   'verbose': -1},\n",
              "  'RandomForestClassifierEntr': {'criterion': 'entropy',\n",
              "   'model_type': 'rf',\n",
              "   'n_estimators': 100,\n",
              "   'n_jobs': -1},\n",
              "  'RandomForestClassifierGini': {'criterion': 'gini',\n",
              "   'model_type': 'rf',\n",
              "   'n_estimators': 100,\n",
              "   'n_jobs': -1},\n",
              "  'weighted_ensemble_k0_l1': {'max_models': 25, 'max_models_per_type': 5}},\n",
              " 'model_paths': {'LightGBMClassifier': 'AutogluonModels/ag-20200201_135935/models/LightGBMClassifier/',\n",
              "  'RandomForestClassifierEntr': 'AutogluonModels/ag-20200201_135935/models/RandomForestClassifierEntr/',\n",
              "  'RandomForestClassifierGini': 'AutogluonModels/ag-20200201_135935/models/RandomForestClassifierGini/',\n",
              "  'weighted_ensemble_k0_l1': 'AutogluonModels/ag-20200201_135935/models/weighted_ensemble_k0_l1/'},\n",
              " 'model_performance': {'LightGBMClassifier': 0.8026969481902059,\n",
              "  'RandomForestClassifierEntr': 0.8005677785663591,\n",
              "  'RandomForestClassifierGini': 0.8026969481902059,\n",
              "  'weighted_ensemble_k0_l1': 0.8090844570617459},\n",
              " 'model_pred_times': {'LightGBMClassifier': 0.020742416381835938,\n",
              "  'RandomForestClassifierEntr': 0.11597776412963867,\n",
              "  'RandomForestClassifierGini': 0.11626601219177246,\n",
              "  'weighted_ensemble_k0_l1': 0.0011415481567382812},\n",
              " 'model_types': {'LightGBMClassifier': 'LGBModel',\n",
              "  'RandomForestClassifierEntr': 'RFModel',\n",
              "  'RandomForestClassifierGini': 'RFModel',\n",
              "  'weighted_ensemble_k0_l1': 'WeightedEnsembleModel'},\n",
              " 'num_bagging_folds': 0,\n",
              " 'num_classes': 2,\n",
              " 'stack_ensemble_levels': 0}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n9Wj5LXzVCkq",
        "colab_type": "code",
        "outputId": "62553fb1-f2b7-48cc-c3f3-09cc1c5f870e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "predictor.fit_summary()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "*** Summary of fit() ***\n",
            "Number of models trained: 11\n",
            "Types of models trained: \n",
            "{'TabularNeuralNetModel', 'KNNModel', 'LGBModel', 'WeightedEnsembleModel', 'CatboostModel', 'RFModel'}\n",
            "Validation performance of individual models: {'RandomForestClassifierGini': 0.7695035460992907, 'RandomForestClassifierEntr': 0.7854609929078015, 'ExtraTreesClassifierGini': 0.7677304964539007, 'ExtraTreesClassifierEntr': 0.7659574468085106, 'KNeighborsClassifierUnif': 0.7730496453900709, 'KNeighborsClassifierDist': 0.7411347517730497, 'LightGBMClassifier': 0.7890070921985816, 'CatboostClassifier': 0.799645390070922, 'NeuralNetClassifier': 0.776595744680851, 'LightGBMClassifierCustom': 0.7783687943262412, 'weighted_ensemble_k0_l1': 0.8049645390070922}\n",
            "Best model (based on validation performance): weighted_ensemble_k0_l1\n",
            "Hyperparameter-tuning used: False\n",
            "Bagging used: False \n",
            "Stack-ensembling used: False \n",
            "User-specified hyperparameters:\n",
            "{'NN': {'num_epochs': 500}, 'GBM': {'num_boost_round': 10000}, 'CAT': {'iterations': 10000}, 'RF': {'n_estimators': 300}, 'XT': {'n_estimators': 300}, 'KNN': {}, 'custom': ['GBM']}\n",
            "Plot summary of models saved to file: SummaryOfModels.html\n",
            "*** End of fit() summary ***\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'feature_prune': False,\n",
              " 'hyperparameter_tune': False,\n",
              " 'hyperparameters_userspecified': {'CAT': {'iterations': 10000},\n",
              "  'GBM': {'num_boost_round': 10000},\n",
              "  'KNN': {},\n",
              "  'NN': {'num_epochs': 500},\n",
              "  'RF': {'n_estimators': 300},\n",
              "  'XT': {'n_estimators': 300},\n",
              "  'custom': ['GBM']},\n",
              " 'model_best': 'weighted_ensemble_k0_l1',\n",
              " 'model_fit_times': {'CatboostClassifier': 3.3552353382110596,\n",
              "  'ExtraTreesClassifierEntr': 1.4251093864440918,\n",
              "  'ExtraTreesClassifierGini': 1.2110621929168701,\n",
              "  'KNeighborsClassifierDist': 0.01639580726623535,\n",
              "  'KNeighborsClassifierUnif': 0.012174129486083984,\n",
              "  'LightGBMClassifier': 0.6526901721954346,\n",
              "  'LightGBMClassifierCustom': 0.9817988872528076,\n",
              "  'NeuralNetClassifier': 23.89044451713562,\n",
              "  'RandomForestClassifierEntr': 1.9158048629760742,\n",
              "  'RandomForestClassifierGini': 1.619532585144043,\n",
              "  'weighted_ensemble_k0_l1': 0.5576424598693848},\n",
              " 'model_hyperparams': {'CatboostClassifier': {'eval_metric': 'Accuracy',\n",
              "   'iterations': 10000,\n",
              "   'learning_rate': 0.1,\n",
              "   'random_seed': 0},\n",
              "  'ExtraTreesClassifierEntr': {'criterion': 'entropy',\n",
              "   'model_type': 'xt',\n",
              "   'n_estimators': 300,\n",
              "   'n_jobs': -1},\n",
              "  'ExtraTreesClassifierGini': {'criterion': 'gini',\n",
              "   'model_type': 'xt',\n",
              "   'n_estimators': 300,\n",
              "   'n_jobs': -1},\n",
              "  'KNeighborsClassifierDist': {'n_jobs': -1, 'weights': 'distance'},\n",
              "  'KNeighborsClassifierUnif': {'n_jobs': -1, 'weights': 'uniform'},\n",
              "  'LightGBMClassifier': {'boosting_type': 'gbdt',\n",
              "   'metric': 'binary_logloss,binary_error',\n",
              "   'num_boost_round': 10000,\n",
              "   'num_threads': -1,\n",
              "   'objective': 'binary',\n",
              "   'two_round': True,\n",
              "   'verbose': -1},\n",
              "  'LightGBMClassifierCustom': {'boosting_type': 'gbdt',\n",
              "   'feature_fraction': 0.9,\n",
              "   'learning_rate': 0.03,\n",
              "   'metric': 'binary_logloss,binary_error',\n",
              "   'min_data_in_leaf': 5,\n",
              "   'num_boost_round': 10000,\n",
              "   'num_leaves': 128,\n",
              "   'num_threads': -1,\n",
              "   'objective': 'binary',\n",
              "   'seed_value': 0,\n",
              "   'two_round': True,\n",
              "   'verbose': -1},\n",
              "  'NeuralNetClassifier': {'activation': 'relu',\n",
              "   'batch_size': 512,\n",
              "   'clip_gradient': 100.0,\n",
              "   'ctx': cpu(0),\n",
              "   'dropout_prob': 0.1,\n",
              "   'embed_exponent': 0.56,\n",
              "   'embedding_size_factor': 1.0,\n",
              "   'epochs_wo_improve': 20,\n",
              "   'layers': [256, 128],\n",
              "   'learning_rate': 0.0003,\n",
              "   'loss_function': SoftmaxCrossEntropyLoss(batch_axis=0, w=None),\n",
              "   'max_embedding_dim': 100,\n",
              "   'max_layer_width': 2056,\n",
              "   'momentum': 0.9,\n",
              "   'network_type': 'widedeep',\n",
              "   'num_dataloading_workers': 1,\n",
              "   'num_epochs': 500,\n",
              "   'numeric_embed_dim': 371,\n",
              "   'optimizer': 'adam',\n",
              "   'proc.embed_min_categories': 4,\n",
              "   'proc.impute_strategy': 'median',\n",
              "   'proc.max_category_levels': 500,\n",
              "   'proc.skew_threshold': 0.99,\n",
              "   'seed_value': None,\n",
              "   'use_batchnorm': True,\n",
              "   'weight_decay': 1e-06,\n",
              "   'y_range': None,\n",
              "   'y_range_extend': 0.05},\n",
              "  'RandomForestClassifierEntr': {'criterion': 'entropy',\n",
              "   'model_type': 'rf',\n",
              "   'n_estimators': 300,\n",
              "   'n_jobs': -1},\n",
              "  'RandomForestClassifierGini': {'criterion': 'gini',\n",
              "   'model_type': 'rf',\n",
              "   'n_estimators': 300,\n",
              "   'n_jobs': -1},\n",
              "  'weighted_ensemble_k0_l1': {'max_models': 25, 'max_models_per_type': 5}},\n",
              " 'model_paths': {'CatboostClassifier': 'AutogluonModels/ag-20200201_133255/models/CatboostClassifier/',\n",
              "  'ExtraTreesClassifierEntr': 'AutogluonModels/ag-20200201_133255/models/ExtraTreesClassifierEntr/',\n",
              "  'ExtraTreesClassifierGini': 'AutogluonModels/ag-20200201_133255/models/ExtraTreesClassifierGini/',\n",
              "  'KNeighborsClassifierDist': 'AutogluonModels/ag-20200201_133255/models/KNeighborsClassifierDist/',\n",
              "  'KNeighborsClassifierUnif': 'AutogluonModels/ag-20200201_133255/models/KNeighborsClassifierUnif/',\n",
              "  'LightGBMClassifier': 'AutogluonModels/ag-20200201_133255/models/LightGBMClassifier/',\n",
              "  'LightGBMClassifierCustom': 'AutogluonModels/ag-20200201_133255/models/LightGBMClassifierCustom/',\n",
              "  'NeuralNetClassifier': 'AutogluonModels/ag-20200201_133255/models/NeuralNetClassifier/',\n",
              "  'RandomForestClassifierEntr': 'AutogluonModels/ag-20200201_133255/models/RandomForestClassifierEntr/',\n",
              "  'RandomForestClassifierGini': 'AutogluonModels/ag-20200201_133255/models/RandomForestClassifierGini/',\n",
              "  'weighted_ensemble_k0_l1': 'AutogluonModels/ag-20200201_133255/models/weighted_ensemble_k0_l1/'},\n",
              " 'model_performance': {'CatboostClassifier': 0.799645390070922,\n",
              "  'ExtraTreesClassifierEntr': 0.7659574468085106,\n",
              "  'ExtraTreesClassifierGini': 0.7677304964539007,\n",
              "  'KNeighborsClassifierDist': 0.7411347517730497,\n",
              "  'KNeighborsClassifierUnif': 0.7730496453900709,\n",
              "  'LightGBMClassifier': 0.7890070921985816,\n",
              "  'LightGBMClassifierCustom': 0.7783687943262412,\n",
              "  'NeuralNetClassifier': 0.776595744680851,\n",
              "  'RandomForestClassifierEntr': 0.7854609929078015,\n",
              "  'RandomForestClassifierGini': 0.7695035460992907,\n",
              "  'weighted_ensemble_k0_l1': 0.8049645390070922},\n",
              " 'model_pred_times': {'CatboostClassifier': 0.025838375091552734,\n",
              "  'ExtraTreesClassifierEntr': 0.1192636489868164,\n",
              "  'ExtraTreesClassifierGini': 0.11608672142028809,\n",
              "  'KNeighborsClassifierDist': 0.10746884346008301,\n",
              "  'KNeighborsClassifierUnif': 0.10909509658813477,\n",
              "  'LightGBMClassifier': 0.018786191940307617,\n",
              "  'LightGBMClassifierCustom': 0.020075082778930664,\n",
              "  'NeuralNetClassifier': 0.23287582397460938,\n",
              "  'RandomForestClassifierEntr': 0.1156458854675293,\n",
              "  'RandomForestClassifierGini': 0.11663198471069336,\n",
              "  'weighted_ensemble_k0_l1': 0.0014667510986328125},\n",
              " 'model_types': {'CatboostClassifier': 'CatboostModel',\n",
              "  'ExtraTreesClassifierEntr': 'RFModel',\n",
              "  'ExtraTreesClassifierGini': 'RFModel',\n",
              "  'KNeighborsClassifierDist': 'KNNModel',\n",
              "  'KNeighborsClassifierUnif': 'KNNModel',\n",
              "  'LightGBMClassifier': 'LGBModel',\n",
              "  'LightGBMClassifierCustom': 'LGBModel',\n",
              "  'NeuralNetClassifier': 'TabularNeuralNetModel',\n",
              "  'RandomForestClassifierEntr': 'RFModel',\n",
              "  'RandomForestClassifierGini': 'RFModel',\n",
              "  'weighted_ensemble_k0_l1': 'WeightedEnsembleModel'},\n",
              " 'num_bagging_folds': 0,\n",
              " 'num_classes': 2,\n",
              " 'stack_ensemble_levels': 0}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7_HGKg57-ONK",
        "colab_type": "code",
        "outputId": "dd9b44cf-5e6e-4b6f-c079-548c3f4da40d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        }
      },
      "source": [
        "predictor.leaderboard()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                        model  score_val  fit_time  pred_time_val  stack_level\n",
            "3     weighted_ensemble_k0_l1   0.809084  0.264182       0.001142            1\n",
            "0  RandomForestClassifierGini   0.802697  0.655841       0.116266            0\n",
            "2          LightGBMClassifier   0.802697  0.445214       0.020742            0\n",
            "1  RandomForestClassifierEntr   0.800568  0.755725       0.115978            0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
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              "      <th>score_val</th>\n",
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              "      <th>3</th>\n",
              "      <td>weighted_ensemble_k0_l1</td>\n",
              "      <td>0.809084</td>\n",
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              "      <th>1</th>\n",
              "      <td>RandomForestClassifierEntr</td>\n",
              "      <td>0.800568</td>\n",
              "      <td>0.755725</td>\n",
              "      <td>0.115978</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        model  score_val  fit_time  pred_time_val  stack_level\n",
              "3     weighted_ensemble_k0_l1   0.809084  0.264182       0.001142            1\n",
              "0  RandomForestClassifierGini   0.802697  0.655841       0.116266            0\n",
              "2          LightGBMClassifier   0.802697  0.445214       0.020742            0\n",
              "1  RandomForestClassifierEntr   0.800568  0.755725       0.115978            0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lX9dvqVl-dUS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}