2.1.Classification.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "2.1.Classification.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "xtdbua_vhb93",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 312
        },
        "outputId": "8cbeac6d-041f-4b27-8ee7-5cc426b9b2d3"
      },
      "source": [
        "!nvidia-smi"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mon Sep 16 11:55:43 2019       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 430.40       Driver Version: 418.67       CUDA Version: 10.1     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   67C    P8    21W /  70W |      0MiB / 15079MiB |      0%      Default |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                       GPU Memory |\n",
            "|  GPU       PID   Type   Process name                             Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fQhDN9d4jz2g",
        "colab_type": "text"
      },
      "source": [
        "## Load Libraries and Import Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LaJASaAicZkk",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "%matplotlib inline\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import sklearn\n",
        "from datetime import datetime\n",
        "import warnings\n",
        "warnings.simplefilter(\"ignore\")\n",
        "\n",
        "from yellowbrick.target import ClassBalance\n",
        "from yellowbrick.classifier import ROCAUC\n",
        "from yellowbrick.classifier import PrecisionRecallCurve\n",
        "from yellowbrick.classifier import ClassificationReport\n",
        "from yellowbrick.classifier import ClassPredictionError\n",
        "from yellowbrick.classifier import DiscriminationThreshold"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "73qgrdKQcdbQ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('ggplot')\n",
        "plt.rcParams['figure.figsize'] = (12, 8)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_4cyA1KKcddr",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "7ee4c531-0e7a-4a68-f899-fefde6b65d83"
      },
      "source": [
        "data = pd.read_csv('./casualty_train.csv')\n",
        "data.head()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "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>casualty_class</th>\n",
              "      <th>gender</th>\n",
              "      <th>age</th>\n",
              "      <th>severe</th>\n",
              "      <th>pedestrian_location</th>\n",
              "      <th>pedestrian_movement</th>\n",
              "      <th>travel</th>\n",
              "      <th>year</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>passenger</td>\n",
              "      <td>female</td>\n",
              "      <td>33</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>motorbike</td>\n",
              "      <td>2007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>passenger</td>\n",
              "      <td>female</td>\n",
              "      <td>20</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>car</td>\n",
              "      <td>2005</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>passenger</td>\n",
              "      <td>male</td>\n",
              "      <td>52</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>car</td>\n",
              "      <td>2006</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>passenger</td>\n",
              "      <td>female</td>\n",
              "      <td>17</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>pedestrian</td>\n",
              "      <td>2012</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>passenger</td>\n",
              "      <td>female</td>\n",
              "      <td>20</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>motorbike</td>\n",
              "      <td>2010</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  casualty_class  gender age  ...  pedestrian_movement      travel  year\n",
              "0      passenger  female  33  ...                  NaN   motorbike  2007\n",
              "1      passenger  female  20  ...                  NaN         car  2005\n",
              "2      passenger    male  52  ...                  NaN         car  2006\n",
              "3      passenger  female  17  ...                  NaN  pedestrian  2012\n",
              "4      passenger  female  20  ...                  NaN   motorbike  2010\n",
              "\n",
              "[5 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZGDtGCOYcdgT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 243
        },
        "outputId": "11c23909-29de-42c8-c1a9-af933a0dc0c2"
      },
      "source": [
        "data.info()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 232835 entries, 0 to 232834\n",
            "Data columns (total 8 columns):\n",
            "casualty_class         232835 non-null object\n",
            "gender                 232835 non-null object\n",
            "age                    232835 non-null object\n",
            "severe                 232835 non-null bool\n",
            "pedestrian_location    43259 non-null object\n",
            "pedestrian_movement    43259 non-null object\n",
            "travel                 232835 non-null object\n",
            "year                   232835 non-null int64\n",
            "dtypes: bool(1), int64(1), object(6)\n",
            "memory usage: 12.7+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CHRvbV1fj3gR",
        "colab_type": "text"
      },
      "source": [
        "## Check for Class Imbalance"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nKA994wocdmk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "outputId": "89bdca15-d1b0-465b-d3b6-420e49595101"
      },
      "source": [
        "y = data.severe.values\n",
        "plt.rcParams['figure.figsize'] = (12, 8)\n",
        "visualizer = ClassBalance(labels=[\"False\", \"True\"])\n",
        "visualizer.fit(y)\n",
        "visualizer.poof()\n",
        "#we will need to perform stratified sampling during train/test split, under the assumption\n",
        "#that the imbalance is present during evaluation too"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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X85w6+7Fjx7R//34dP35cs2fPlmVZysvL82rpTteuXRUaGqqUlBTP2uJJkybJ6XQqKChI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\nYII=\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vGHS-RugcdoZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 156
        },
        "outputId": "e49e7cd8-21aa-4eaa-c531-4ce30f3112e6"
      },
      "source": [
        "print(data.casualty_class.unique())\n",
        "print(data.travel.unique())\n",
        "print(data.pedestrian_location.unique())\n",
        "print(data.pedestrian_movement.unique())\n",
        "print(data.year.unique())"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['passenger' 'pedestrian' 'driver']\n",
            "['motorbike' 'car' 'pedestrian' 'bicycle' 'taxi' 'bus' 'other']\n",
            "[nan 'In road' 'Close to Crossing' 'Not on Crossing' 'Unknown'\n",
            " 'Pedestrian Crossing' 'Footpath' 'Zig-Zag']\n",
            "[nan 'In Rd Not Crossing' 'Drivers N/Side' 'Unknown Or Other'\n",
            " 'Drivers N/Side Msk' 'Drivers O/Side' 'Back To Traffic'\n",
            " 'Drivers O/Side Msk' 'Facing Traffic' 'In Rd Not Crossing Msk']\n",
            "[2007 2005 2006 2012 2010 2008 2011 2009 2014 2013]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tDn-RTA56E_w",
        "colab_type": "text"
      },
      "source": [
        "## Data Preprocessing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "30U9qHjbcdrP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 244
        },
        "outputId": "6d95ef6c-5cd4-4fdb-de39-6fcdd4b45a26"
      },
      "source": [
        "from sklearn.preprocessing import OrdinalEncoder\n",
        "from sklearn.preprocessing import LabelEncoder, StandardScaler\n",
        "\n",
        "data.age = OrdinalEncoder().fit_transform(np.array(data.age).reshape(-1,1))\n",
        "data = pd.get_dummies(data, columns=['casualty_class', 'gender', 'year', 'pedestrian_location',\n",
        "                                     'pedestrian_movement', 'travel'])\n",
        "data.severe = LabelEncoder().fit_transform(data.severe)\n",
        "\n",
        "data.head()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "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>age</th>\n",
              "      <th>severe</th>\n",
              "      <th>casualty_class_driver</th>\n",
              "      <th>casualty_class_passenger</th>\n",
              "      <th>casualty_class_pedestrian</th>\n",
              "      <th>gender_female</th>\n",
              "      <th>gender_male</th>\n",
              "      <th>year_2005</th>\n",
              "      <th>year_2006</th>\n",
              "      <th>year_2007</th>\n",
              "      <th>year_2008</th>\n",
              "      <th>year_2009</th>\n",
              "      <th>year_2010</th>\n",
              "      <th>year_2011</th>\n",
              "      <th>year_2012</th>\n",
              "      <th>year_2013</th>\n",
              "      <th>year_2014</th>\n",
              "      <th>pedestrian_location_Close to Crossing</th>\n",
              "      <th>pedestrian_location_Footpath</th>\n",
              "      <th>pedestrian_location_In road</th>\n",
              "      <th>pedestrian_location_Not on Crossing</th>\n",
              "      <th>pedestrian_location_Pedestrian Crossing</th>\n",
              "      <th>pedestrian_location_Unknown</th>\n",
              "      <th>pedestrian_location_Zig-Zag</th>\n",
              "      <th>pedestrian_movement_Back To Traffic</th>\n",
              "      <th>pedestrian_movement_Drivers N/Side</th>\n",
              "      <th>pedestrian_movement_Drivers N/Side Msk</th>\n",
              "      <th>pedestrian_movement_Drivers O/Side</th>\n",
              "      <th>pedestrian_movement_Drivers O/Side Msk</th>\n",
              "      <th>pedestrian_movement_Facing Traffic</th>\n",
              "      <th>pedestrian_movement_In Rd Not Crossing</th>\n",
              "      <th>pedestrian_movement_In Rd Not Crossing Msk</th>\n",
              "      <th>pedestrian_movement_Unknown Or Other</th>\n",
              "      <th>travel_bicycle</th>\n",
              "      <th>travel_bus</th>\n",
              "      <th>travel_car</th>\n",
              "      <th>travel_motorbike</th>\n",
              "      <th>travel_other</th>\n",
              "      <th>travel_pedestrian</th>\n",
              "      <th>travel_taxi</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>27.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>13.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>48.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>13.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    age  severe  ...  travel_pedestrian  travel_taxi\n",
              "0  27.0       0  ...                  0            0\n",
              "1  13.0       0  ...                  0            0\n",
              "2  48.0       0  ...                  0            0\n",
              "3   9.0       0  ...                  1            0\n",
              "4  13.0       0  ...                  0            0\n",
              "\n",
              "[5 rows x 40 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PNuIOY-i6IiU",
        "colab_type": "text"
      },
      "source": [
        "## Create Train/Test Sets"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MhImaQ-Jcdto",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "dfd6f3a0-68f4-4e85-b6b2-21cf26c8fc3a"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "y = data.severe\n",
        "X = data.loc[:, data.columns != 'severe']\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1)\n",
        "X_train.shape, X_test.shape, y_train.shape, y_test.shape"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((186268, 39), (46567, 39), (186268,), (46567,))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tlZcQRN-cd1q",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 139
        },
        "outputId": "cffac7c0-8223-43ca-9735-d8680387e53d"
      },
      "source": [
        "import xgboost as xgb\n",
        "\n",
        "clf = xgb.XGBClassifier(learning_rate=0.1,\n",
        "                        n_estimators=200,\n",
        "                        min_child_weight=8,\n",
        "                        scale_pos_weight=1,\n",
        "                        objective= 'binary:logistic',\n",
        "                        seed=27,\n",
        "                        tree_method='gpu_hist',\n",
        "                        metric='error')\n",
        "clf.fit(X_train, y_train)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
              "              colsample_bynode=1, colsample_bytree=1, gamma=0,\n",
              "              learning_rate=0.1, max_delta_step=0, max_depth=3, metric='error',\n",
              "              min_child_weight=8, missing=None, n_estimators=200, n_jobs=1,\n",
              "              nthread=None, objective='binary:logistic', random_state=0,\n",
              "              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=27,\n",
              "              silent=None, subsample=1, tree_method='gpu_hist', verbosity=1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0lMKkdnrcd43",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "7ea8b49c-f0f1-4cac-cd68-03d375dd45a0"
      },
      "source": [
        "y_pred = clf.predict(X_test)\n",
        "\n",
        "from sklearn.metrics import accuracy_score\n",
        "print(\"Test Accuracy: \", accuracy_score(y_test, y_pred))"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Test Accuracy:  0.891296411621964\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QlXHIXYjceAa",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        },
        "outputId": "546c86e3-194a-460c-b5d4-8fa2c306f9ba"
      },
      "source": [
        "visualizer = ClassificationReport(clf, classes=[\"Not Severe\", \"Severe\"], support=True)\n",
        "\n",
        "visualizer.fit(X_train, y_train)        # Fit the visualizer and the model\n",
        "visualizer.score(X_test, y_test)        # Evaluate the model on the test data\n",
        "visualizer.poof()    "
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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f13e+8x2Fh7PbHIMPW5hwU8FgUHl5eZo9e7bu\nu+++G17705/+pKamJm3atMmi6TBcdHZ2qri4WH6/X9nZ2ZKky5cva9q0adzzAGDYOH78uF599VX9\n5je/UUtLi3bs2KFHH31USUlJ2r59u37xi1/ovvvuU1tbmxwOBzdPY9AiIPAl//k8/rfeekvt7e16\n5plnJEler1fFxcV6+umnVVdXp8mTJ1s1KoaRjo4OHT58WD6fT8uXL1diYqLVIwHALdHQ0KCoqChF\nRkbqxIkT2rlzp9avX6/W1lZt2bJFmZmZWrZsmRITE7/0GQwMRmysww3637jKy8v1wQcf6OjRo1q6\ndKkiIyO1Z88eSRr45d9gMEg84JZxuVxasGCBJkyYIKfTafU4APCt9F+fvXTpkg4ePKgDBw4oEAgo\nOztba9as0R/+8AfFxsZq3bp1qqioUDAYtHhiwBwrEPiS0tJSvffee1q6dKk++OADzZgxQ5mZmdqz\nZ496e3vV3t6uVatW8WNeuC144giA4aKsrEz79+9XWlqaOjo6FBUVpYceekijRo3S1q1bVVpaqi1b\ntugf//iHjh49qhdffFEjRoywemzgfyIg8CV5eXnKzMxUV1eX3n//ff3qV79Sd3e3xowZo9raWjmd\nTrndbpZZAQD4L6qrq7Vjxw6tXbtWMTExqq6uVlNTk65du6YpU6bozJkzys7O1oQJEyRJXV1d3POA\nIYOAwEAIXLhwQT6fT01NTfL5fAoEAnriiScUHx+vd955Rz/60Y+4MgIAgAGv16tPP/1UkyZNUnt7\nu06fPq3IyEhdunRJPT09ys3NVUZGxsCqKxflMJTwbDAMPFru8OHDWrZsmZKTk1VSUqIf/vCHio+P\nV1VVlU6cOKF58+YpPj7e6nEBABj0xo0bpzNnzqioqEirVq3SnDlzdO7cOblcLk2cOFGjRo2S9P+/\n80A8YChhBeIu1n+1o62tTfv375fH49FTTz2l6dOnq7y8XO+8847i4uJ04cIFPfbYY0pPT7d6ZAAA\nhqTy8nLt3btXOTk5/G4ShjwC4i536tQp5eXlKS4uTp9++qncbrc2bNighIQENTc3y263q7u7W+PG\njbN6VAAAhpxAIKAjR47o6NGjeuSRR5SRkWH1SMC3RkDcxXw+n/Ly8rRmzRq53W5t27ZNRUVFmjp1\nqp555hklJCRYPSIAAENeMBhUIBCQy+WyehTgluBZiXepYDCokydPyufzye/3S5Jyc3OVmZmpuro6\nvfzyy7p27ZrFUwIAMPSFh4cTDxhWuIn6LhUeHq5Fixbp+vXrOnHihMLCwpSamqqFCxcqPT1ds2bN\n0j333GP1mAAAABhk2MJ0l+vo6FBxcbE8Ho8yMzP173//Wz/+8Y/ZowkAAICvREBAnZ2dys/P12ef\nfaasrCwtWLCA51EDAADgK3EPBBQVFaWlS5cqNTVVZ86c0fnz54kHAAAAfCUCApIkl8ulBQsWKCkp\nSTExMVaPAwAAgEGKLUy4QSgUGvhVTAAAAOA/ERAAAAAAjHGpGQAAAIAxAgIAAACAMQICAAAAgDEC\nAgAAAICx/wPtr/Hak5arJgAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p2YEpXUgceDk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 516
        },
        "outputId": "c5950489-ee3e-49e9-97d4-de797551524f"
      },
      "source": [
        "visualizer = ROCAUC(clf, classes=[\"Not Severe\", \"Severe\"])\n",
        "\n",
        "visualizer.fit(X_train, y_train)        \n",
        "visualizer.score(X_test, y_test)        \n",
        "visualizer.poof()                      "
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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rSmShbKildJ4mYP7nj9PPXQreZsbE9qKvuxTLiLEokyZByhxIzehywfRBPp8P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6hxKZJk85BWTzkcqMXPoH7+DgKC0CbehDb4lAbPPVhs44FV+ym3OdhbWE3/hOA6x6sdBo+vzaK8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\niIhIHf0BbIJtF9ByivoAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-i1MhFszceFT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        },
        "outputId": "127ac04d-4c3c-4212-9c68-524cc5fdfe86"
      },
      "source": [
        "visualizer = ClassPredictionError(clf, classes=[\"Not Severe\", \"Severe\"])\n",
        "visualizer.fit(X_train, y_train)\n",
        "visualizer.score(X_test, y_test)\n",
        "visualizer.poof()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ycnJyJP0+HSYsLEzvv/9+ia/d0gJ0SXJzcyVJbdu2lbe3d4nrYefm5ioiIkI7duy4Ytu+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\ngg==\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b8PyPrIAceKI",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 516
        },
        "outputId": "9ea32605-7df4-4152-c448-390a8297be90"
      },
      "source": [
        "visualizer = DiscriminationThreshold(clf)\n",
        "\n",
        "visualizer.fit(X_test, y_test)\n",
        "visualizer.poof()  "
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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uvPJK5s6dGz7J0Wg0cuWVV7JgwQJuv/12zGYz9913H1lZWSxevJjevXtzxRVX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BM8//zzXLhw4Y7LHDp0iH/5l39henqadDq9GGAvJ4SgqcVgYqyGrE8609ruZd4nRmuUS14Zy9yU\ni68KzWGNqAaDFZeaHxaqVKQUjJQCRI0apuZAdga+/bXFdfpOnKEajkNn9+4PrgERCOy+khVl4xYG\nMYYjiJZ2EGL1/9dky7oG18qpcVCDWRVFUfY8FWBvgYUJVwp5F8eWzKZshgaqSAkdXV5JyN2CK90Q\nBIKCaFzfdYGYZVm0tbVx48aNxTIRbZUppzVd4A9o2DVJrbbUjlAIQUOjQUOjd/oVCy5XzpepZkDk\n4LAheasq6K9Kji2bC2TO0ZkbnCD67vfR82mvpa3Pgk/8T4Q7u0in01v/5O9AxBLIbBph+iAQROYy\nXnZztdkCQ9Ht30Fl0y1+WhSJeTNDrrVcS/u61ienJ0He4+ySiqIoyq6xwTYVynrkMi65jINjSzJp\nm5vzwXV7l0lLu7lmwGyYgkSjQWOrQUu7QSxx90B8pxw4cACAyclJstnsmsslkjrNbSa+OwzcDIY0\nDh/3yiWkq3PCCKAhOV+tf4wozdHw2tcxcikQgrmTv0nlE/8LIrRy6vDtJgwDDhz2vje2eIMXAbp6\nVn9AY/P27ZyyZ+zSl7uiKIqyQSqDvclKRZf8nJeBKuQdblyrgoTeoxaxeP3gwYXWebEGHWT9tOY7\n5fOf//y6ljt48CCvvfYa09PTTE9PEw6HMVdpM7dwgRCK6DiOd9FxO5mdJZSe4XBc41qmDaMao0uv\ncNNxSTuQmD9sHYNvAGAHY0z9t/+bN8mHhFClQtgRSLkzAYrwB73SFMuPPPUhr1VLatIrlG9sQWRm\nkellM/5pOuyCiwJFURRFUbbGzkd095FiwWV22gYJqSmb65cqSAm9R1YJrgU0tRg0t5lYlrYrgmuA\nL3zhC+tazu/309bWRqFQIJPJkEql7rh8MKQRia3xHLNppG0TNKo0BTKA4MN6BBC8URIkxy/xxPf/\nD7qvvUrVijD9e//WC17xqk7yNYuRbICJYmzLyldFIonoObJYRysWWgACHDyGSDZ5t5um16ItEETE\nGhCaDrf13haBIGKVkhpFUSlsRVGU+4N6l98E0vXa8KVTNlJKRoerDA9WcV3oOuAjlqgPri2/oLHV\nwPTtvsP/zDPPrHvZU6dOATA6Osrc3By2bd9x+WDQ68W9QBbzyJGbXv/qeW3BLLpeJeQG+WOjFb8T\nInzxR/iqBQAufOgPmRWBVdfvSkHVXbsF4d3UBc236+qBWAIO93n1tD1HEIlGhOVHhFYZvBZvgEPH\nvZ+tAKK5HZFs9uqzE6tPMa8oiqIoyv1BlYh8QHZNkk07VMoSKSX9VyrMZV18PkFXj4/obZnrYFgj\nltA33Pd6u0xPT6972Z6eHvx+P+Pj4xw6dIhsNksymVxzeaF5vbKnJmpe/+rJsRUDADUBLcFZxvJN\nIHU+rEf5+Zn/naxzmWKkmWoghuZIYoa76tVhzTWw9I0NEhOGiXRsiMYRwTByYsTLQrsSQmFkNg0+\n/2LWWXb1IjQN2X0IxofXeK7asvUbyH3dMJuCaAwaWze0f8qDZHf+Xbh/qOOrKMr2UAH2B1CrukxP\n2Ejp9bu+cb3KXNYlGNLoPWLVz8goIDQfXO/WgYsbpWkaJ0+e5Ne//jWjo6MEg8E7BtgApk/Q3GpS\nGBpnznHQhMSn2ZQdr37byExy5P0f0e5qBHNpXn7839FoNTNuWvh9BQRepjprayQMd8X6y7aJQBI0\nqnf/tF0IRO8xiEQR05MQCnvt1vwBr1WaXYOO/Ygr79cHzPM/C9NEdh5Y17EShgnNbetaVlEURVGU\nvU0F2PeoXHKZTXnBtZSSocEq2bSDYcKBQ7664Nr0CRJJfVeWhNzu+PHjG1r+zJkzvP322wwPD7N/\n/35qtdqqgx0XSCkxJm8SmRmmpEVIWEVsV6fsmISuvUHsne8DEAAq/iizYhqfbCdQi1GuxdDNPD4r\nx5StEdFdbm8PXnEMKo6B7erErFLdfaK5zeszjBccc6jPa68GyOY2b9IQTYOWdi/Dbte8GTEPHFrz\n+ahaamVT3R/X3oqiKA88FWDfg0LeITPjlSF4Ndc10imHYEjj0HELffnU5ZG9lbV+6aWXNrS83++n\np6eH/v5+ZmZmaGlpIZFIrP2AyTHk2DBCQHNgzssyz2VpfP1FfFNDAFQbOpjseZyhxqMcsnS+nZ3l\n43ojmhA4tTCuWUTTbDKORuMqWWyAou3Db9SwdK8uXERisL/Xq7MeGvB+Xta3WNx2USCEANNrHSj8\nu3/iGkVRFEVRdg+VftugUtElO+sF17WqZPBalalxG58l6D2yFFwv9LSON+zeXtareeGFFzb8mIcf\nfhiAW7dukclkvOzvKmSljBweWPxdCO828+//w2JwnXn0vyf1O3+C03uGmj+CKcDVbF5yJhHCC5Yr\nxWbKhWZmaiZld/Vj60pBuhyk5mheb+qeIwhNRySb4cBhiDVs+HkqytbbO38rFEVRlLWpAHudpJTk\nMs5iWYhtS/qvlMmmHfwBwcFjSzXXmg4NjQbB0N47vN/+9rc3/JiFrPX09DS5XI5MJrP6gqnJummg\nZWYW/uYrXt9ogN99DufwaXTNxScksfnBikkd8kDel0JoXscRKQ0q5TipmsZanflcf5iZUC/Oqce9\nuup5IpH0gm5FURRFUZQtsPciwB3g2JKZaZu5rAMSqhWXaxfLlIqSZJPOsVN+/PN9rDUdGpvN+gGO\n9zkhBH19fUgpGRkZIZfLrb5ganLxR+m68NbPvV/CUfjMFxGd+2kM5ImaZQASuhc6H/F539+rSfzB\nFD6/N2mL6/hJl5Kka8tO4/nuLMLQoX0fMt7I1IRDrequmVlXFEVRFEXZTCrAvgPpSvJzDlMTNSol\nLzjLzNpcPl+mXJI0tRp09fgWS0B0Q5BsNh6o4HpBX18fhmEwMjJCsVgkn8sibRtZLCDHhpHnfo0s\ne4MO5WwKvvM1uHkdGprgU3+E8FmL6woYVYJGFVPzjnm3AXFNcrUKRRd0o4K/MYswXBw7wHCuk2K4\nHRFPILp6EYEgJFsQ8023pQtTEzblkgqwlV3uXsvJ9lAZ2o5Sh0lRlG2iPidfheNI5rIOxYKLdJdu\nGx2qkZry6oA79ps0t3r11ZoOsYRBICAQu7S/9Xq98sor9/Q4y7I4cOAA169fZ3rgOomJYUKxCLJW\nq1tOlorw2vchm4a2ffCxj6/oxCEExKwifqPGZC1CztE5ZUleL2m8Vhb8XtxERGNYIailbJyCwXuX\nqpx4uAXTEMjmNm9Cl7oNe/XzgaC6plTuP0LXkXeZ6ElRFEXZPiramCelpFp1yczYTI7VKMx5wbXr\nSqbGa1x8r0RqysYfEBzus2hpMxFCYPoETa0mwZC254NrgEuXLt3T46TrcDrhzWh4a3yCUrW6Mri+\n8j68+O9hZhriSfj9TyIs/6rr0wQEjBrdwTlAcsIHTTr0VyETiHg9rA2Br9VEC3ql3YPXKriuXBlc\nzyuXXOyaymIru9i9/gnR7n0GU0VRFGXzPfAZbOlKSiUvY708+KpWXabGbGZTNguJoeY2g/Z9Jpom\nEAL8Qa8F3/K2fHvdF7/4RS5cuHDX5eTCwMRK2autLszRKlwaAhYzpTLpUoXOqIuuaUi7Bq/9E9y4\nBv4AnDwLR06uq7tK0lcjorvMOToPR338MF3l/VyZj/qXSkp8zVC+CYU5l8vvlzl+2r/quqULczmH\nRPKBP+2V+43qx64oirKrPLCRhuNIinmXuZyzWAYCXiZ7dtphdLiKbYNhQEu7QUubiWEuBW2xhE4o\n8gBnjcZHkGNDSx1A5h1rauAXw+MMZXL0NMSIzKXhn/8Rinlvgd/5A8RdZjQU0ThUSqAbiFCEtrYG\n5iYEvZpBaG6Ki5kiJ+MhEj7v9BW6INZjkR0sUyl709UfPGqtGmSXS95gx73UOlF5kNzDeanp9/Y4\nRVEUZctsS4D9ta99jevXryOE4LOf/SwHDx5cvO/ChQt84xvfQNM02tra+JM/+RO0u2Rj5rLOve+M\ngErZpVKWLO/v5jiSbNphetKmMOciBHTuN2lsMdBuK/14kINrWZgDx4HUxIrgGrwA+92xKW7l5ij/\n6HtEJrz+1uw7AL/18Tu2xxOtHdDS4WXjXHextV68bKNlClCDsw1hXpvKcTlb5DeaoouPNcM6ZjPU\npmAu6zI0WGX/sgGoC1wHCnmX8AP6/6fscvdw4Sd0lb1WFEXZbbY8wL506RITExN8+ctfZmRkhK9+\n9at8+ctfXrz/r//6r/nSl75EMpnkL//yL3nvvfcWJy5ZSy7zAQLs25TLLjNTNqkpG2e+FCSW0Ons\nNrGs+jcuTYd4g3FfD5T70pe+tOZ9cnQYJm555SGrBNcA1uw0j998n1c6+xiUOo2ajvjQRxAnHrnj\ndkVLO2L/wVXvC5gaRkzgViRH3ACvTeW4ka/weKNEWxaQGBFBKCYoj3ifQiSbXCLRlYF0dtahWpE0\nND6wH+Ao9xNNUwlsRVGUXWbLI4zz58/z6KOPAtDZ2UmhUKBYLBIMetNP//mf//niz9FolHw+v9W7\nhOtK0imv/V6p6KWxNR2aWw1vgphwfQBtmIJwVCMQ0NDuo3rr1Xzyk5+s+13aNkyMQDrldQBZa5bG\nUhF+9Tr0X+Yg8Hr7Ua40dtH+0KPs6+y44zZFohHRfWjN+01dw9IFFQuCYY3eiMXAXIWJUo32YP2A\nxoorae8yGbxaJZ1yVg2wAUoFl5zhEIlpqlxE2duE+jRm/dRrXVGU7bHlAXYmk6Gnp2fx92g0SiaT\nWQyqF76n02nOnTvH888/f9d1XrvoTUQiF/+5/We5+u3SKxGozQ9mFAKicY1E0iCR1FeUgiAgEtWJ\nRO+PDiHrc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q+/K+bDmq+vFkLw+4fjCOCfrqdx3KVUddmWXJ4uEU1o+INaXRZQNwTJJu//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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}