potential_asteroid_collison.ipynb

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  "metadata": {
    "colab": {
      "name": "potential_asteroid_collison.ipynb",
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qwRbgwl2Tyj4",
        "outputId": "66f840fc-b2ac-46d0-a3f9-dabd5fbed3bc"
      },
      "source": [
        "pip install catboost"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: catboost in /usr/local/lib/python3.7/dist-packages (1.0.1)\n",
            "Requirement already satisfied: numpy>=1.16.0 in /usr/local/lib/python3.7/dist-packages (from catboost) (1.19.5)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (from catboost) (1.4.1)\n",
            "Requirement already satisfied: plotly in /usr/local/lib/python3.7/dist-packages (from catboost) (4.4.1)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.7/dist-packages (from catboost) (3.2.2)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from catboost) (1.15.0)\n",
            "Requirement already satisfied: graphviz in /usr/local/lib/python3.7/dist-packages (from catboost) (0.10.1)\n",
            "Requirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.7/dist-packages (from catboost) (1.1.5)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->catboost) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->catboost) (2018.9)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->catboost) (1.3.2)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->catboost) (2.4.7)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib->catboost) (0.10.0)\n",
            "Requirement already satisfied: retrying>=1.3.3 in /usr/local/lib/python3.7/dist-packages (from plotly->catboost) (1.3.3)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X7SIw7YzWUOt"
      },
      "source": [
        "## Importing the Libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6A7yf5i8DpwC"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "import tensorflow as tf\n",
        "import seaborn as sns\n",
        "from sklearn.metrics import accuracy_score,classification_report,confusion_matrix\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.ensemble import AdaBoostClassifier\n",
        "from catboost import CatBoostClassifier\n",
        "from xgboost import XGBClassifier\n",
        "from sklearn.ensemble import GradientBoostingClassifier\n",
        "from sklearn.model_selection import cross_val_score"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XyeiYXR0WYLO"
      },
      "source": [
        "## Importing the CSV file"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 360
        },
        "id": "8eImpImCEAna",
        "outputId": "a25d96c5-d0a8-4818-dfb2-9e51609b5bf6"
      },
      "source": [
        "df = pd.read_csv('nasa.csv')\n",
        "df.head(5)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Neo Reference ID</th>\n",
              "      <th>Name</th>\n",
              "      <th>Absolute Magnitude</th>\n",
              "      <th>Est Dia in KM(min)</th>\n",
              "      <th>Est Dia in KM(max)</th>\n",
              "      <th>Est Dia in M(min)</th>\n",
              "      <th>Est Dia in M(max)</th>\n",
              "      <th>Est Dia in Miles(min)</th>\n",
              "      <th>Est Dia in Miles(max)</th>\n",
              "      <th>Est Dia in Feet(min)</th>\n",
              "      <th>Est Dia in Feet(max)</th>\n",
              "      <th>Close Approach Date</th>\n",
              "      <th>Epoch Date Close Approach</th>\n",
              "      <th>Relative Velocity km per sec</th>\n",
              "      <th>Relative Velocity km per hr</th>\n",
              "      <th>Miles per hour</th>\n",
              "      <th>Miss Dist.(Astronomical)</th>\n",
              "      <th>Miss Dist.(lunar)</th>\n",
              "      <th>Miss Dist.(kilometers)</th>\n",
              "      <th>Miss Dist.(miles)</th>\n",
              "      <th>Orbiting Body</th>\n",
              "      <th>Orbit ID</th>\n",
              "      <th>Orbit Determination Date</th>\n",
              "      <th>Orbit Uncertainity</th>\n",
              "      <th>Minimum Orbit Intersection</th>\n",
              "      <th>Jupiter Tisserand Invariant</th>\n",
              "      <th>Epoch Osculation</th>\n",
              "      <th>Eccentricity</th>\n",
              "      <th>Semi Major Axis</th>\n",
              "      <th>Inclination</th>\n",
              "      <th>Asc Node Longitude</th>\n",
              "      <th>Orbital Period</th>\n",
              "      <th>Perihelion Distance</th>\n",
              "      <th>Perihelion Arg</th>\n",
              "      <th>Aphelion Dist</th>\n",
              "      <th>Perihelion Time</th>\n",
              "      <th>Mean Anomaly</th>\n",
              "      <th>Mean Motion</th>\n",
              "      <th>Equinox</th>\n",
              "      <th>Hazardous</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3703080</td>\n",
              "      <td>3703080</td>\n",
              "      <td>21.6</td>\n",
              "      <td>0.127220</td>\n",
              "      <td>0.284472</td>\n",
              "      <td>127.219879</td>\n",
              "      <td>284.472297</td>\n",
              "      <td>0.079051</td>\n",
              "      <td>0.176763</td>\n",
              "      <td>417.388066</td>\n",
              "      <td>933.308089</td>\n",
              "      <td>1995-01-01</td>\n",
              "      <td>788947200000</td>\n",
              "      <td>6.115834</td>\n",
              "      <td>22017.003799</td>\n",
              "      <td>13680.509944</td>\n",
              "      <td>0.419483</td>\n",
              "      <td>163.178711</td>\n",
              "      <td>62753692.0</td>\n",
              "      <td>38993336.0</td>\n",
              "      <td>Earth</td>\n",
              "      <td>17</td>\n",
              "      <td>2017-04-06 08:36:37</td>\n",
              "      <td>5</td>\n",
              "      <td>0.025282</td>\n",
              "      <td>4.634</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.425549</td>\n",
              "      <td>1.407011</td>\n",
              "      <td>6.025981</td>\n",
              "      <td>314.373913</td>\n",
              "      <td>609.599786</td>\n",
              "      <td>0.808259</td>\n",
              "      <td>57.257470</td>\n",
              "      <td>2.005764</td>\n",
              "      <td>2.458162e+06</td>\n",
              "      <td>264.837533</td>\n",
              "      <td>0.590551</td>\n",
              "      <td>J2000</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3723955</td>\n",
              "      <td>3723955</td>\n",
              "      <td>21.3</td>\n",
              "      <td>0.146068</td>\n",
              "      <td>0.326618</td>\n",
              "      <td>146.067964</td>\n",
              "      <td>326.617897</td>\n",
              "      <td>0.090762</td>\n",
              "      <td>0.202951</td>\n",
              "      <td>479.225620</td>\n",
              "      <td>1071.581063</td>\n",
              "      <td>1995-01-01</td>\n",
              "      <td>788947200000</td>\n",
              "      <td>18.113985</td>\n",
              "      <td>65210.346095</td>\n",
              "      <td>40519.173105</td>\n",
              "      <td>0.383014</td>\n",
              "      <td>148.992630</td>\n",
              "      <td>57298148.0</td>\n",
              "      <td>35603420.0</td>\n",
              "      <td>Earth</td>\n",
              "      <td>21</td>\n",
              "      <td>2017-04-06 08:32:49</td>\n",
              "      <td>3</td>\n",
              "      <td>0.186935</td>\n",
              "      <td>5.457</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.351674</td>\n",
              "      <td>1.107776</td>\n",
              "      <td>28.412996</td>\n",
              "      <td>136.717242</td>\n",
              "      <td>425.869294</td>\n",
              "      <td>0.718200</td>\n",
              "      <td>313.091975</td>\n",
              "      <td>1.497352</td>\n",
              "      <td>2.457795e+06</td>\n",
              "      <td>173.741112</td>\n",
              "      <td>0.845330</td>\n",
              "      <td>J2000</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2446862</td>\n",
              "      <td>2446862</td>\n",
              "      <td>20.3</td>\n",
              "      <td>0.231502</td>\n",
              "      <td>0.517654</td>\n",
              "      <td>231.502122</td>\n",
              "      <td>517.654482</td>\n",
              "      <td>0.143849</td>\n",
              "      <td>0.321655</td>\n",
              "      <td>759.521423</td>\n",
              "      <td>1698.341531</td>\n",
              "      <td>1995-01-08</td>\n",
              "      <td>789552000000</td>\n",
              "      <td>7.590711</td>\n",
              "      <td>27326.560182</td>\n",
              "      <td>16979.661798</td>\n",
              "      <td>0.050956</td>\n",
              "      <td>19.821890</td>\n",
              "      <td>7622911.5</td>\n",
              "      <td>4736657.5</td>\n",
              "      <td>Earth</td>\n",
              "      <td>22</td>\n",
              "      <td>2017-04-06 09:20:19</td>\n",
              "      <td>0</td>\n",
              "      <td>0.043058</td>\n",
              "      <td>4.557</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.348248</td>\n",
              "      <td>1.458824</td>\n",
              "      <td>4.237961</td>\n",
              "      <td>259.475979</td>\n",
              "      <td>643.580228</td>\n",
              "      <td>0.950791</td>\n",
              "      <td>248.415038</td>\n",
              "      <td>1.966857</td>\n",
              "      <td>2.458120e+06</td>\n",
              "      <td>292.893654</td>\n",
              "      <td>0.559371</td>\n",
              "      <td>J2000</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3092506</td>\n",
              "      <td>3092506</td>\n",
              "      <td>27.4</td>\n",
              "      <td>0.008801</td>\n",
              "      <td>0.019681</td>\n",
              "      <td>8.801465</td>\n",
              "      <td>19.680675</td>\n",
              "      <td>0.005469</td>\n",
              "      <td>0.012229</td>\n",
              "      <td>28.876199</td>\n",
              "      <td>64.569144</td>\n",
              "      <td>1995-01-15</td>\n",
              "      <td>790156800000</td>\n",
              "      <td>11.173874</td>\n",
              "      <td>40225.948191</td>\n",
              "      <td>24994.839864</td>\n",
              "      <td>0.285322</td>\n",
              "      <td>110.990387</td>\n",
              "      <td>42683616.0</td>\n",
              "      <td>26522368.0</td>\n",
              "      <td>Earth</td>\n",
              "      <td>7</td>\n",
              "      <td>2017-04-06 09:15:49</td>\n",
              "      <td>6</td>\n",
              "      <td>0.005512</td>\n",
              "      <td>5.093</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.216578</td>\n",
              "      <td>1.255903</td>\n",
              "      <td>7.905894</td>\n",
              "      <td>57.173266</td>\n",
              "      <td>514.082140</td>\n",
              "      <td>0.983902</td>\n",
              "      <td>18.707701</td>\n",
              "      <td>1.527904</td>\n",
              "      <td>2.457902e+06</td>\n",
              "      <td>68.741007</td>\n",
              "      <td>0.700277</td>\n",
              "      <td>J2000</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3514799</td>\n",
              "      <td>3514799</td>\n",
              "      <td>21.6</td>\n",
              "      <td>0.127220</td>\n",
              "      <td>0.284472</td>\n",
              "      <td>127.219879</td>\n",
              "      <td>284.472297</td>\n",
              "      <td>0.079051</td>\n",
              "      <td>0.176763</td>\n",
              "      <td>417.388066</td>\n",
              "      <td>933.308089</td>\n",
              "      <td>1995-01-15</td>\n",
              "      <td>790156800000</td>\n",
              "      <td>9.840831</td>\n",
              "      <td>35426.991794</td>\n",
              "      <td>22012.954985</td>\n",
              "      <td>0.407832</td>\n",
              "      <td>158.646713</td>\n",
              "      <td>61010824.0</td>\n",
              "      <td>37910368.0</td>\n",
              "      <td>Earth</td>\n",
              "      <td>25</td>\n",
              "      <td>2017-04-06 08:57:58</td>\n",
              "      <td>1</td>\n",
              "      <td>0.034798</td>\n",
              "      <td>5.154</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.210448</td>\n",
              "      <td>1.225615</td>\n",
              "      <td>16.793382</td>\n",
              "      <td>84.629307</td>\n",
              "      <td>495.597821</td>\n",
              "      <td>0.967687</td>\n",
              "      <td>158.263596</td>\n",
              "      <td>1.483543</td>\n",
              "      <td>2.457814e+06</td>\n",
              "      <td>135.142133</td>\n",
              "      <td>0.726395</td>\n",
              "      <td>J2000</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Neo Reference ID     Name  ...  Equinox  Hazardous\n",
              "0           3703080  3703080  ...    J2000       True\n",
              "1           3723955  3723955  ...    J2000      False\n",
              "2           2446862  2446862  ...    J2000       True\n",
              "3           3092506  3092506  ...    J2000      False\n",
              "4           3514799  3514799  ...    J2000       True\n",
              "\n",
              "[5 rows x 40 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-CF6Shxz2KaD"
      },
      "source": [
        "## Looking for missing values and datatype"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ss1KacwzOaKg",
        "outputId": "355abe25-8439-47f3-8cfc-b2078d1b039e"
      },
      "source": [
        "df.dropna(axis = 0,how = 'any',inplace = True)\n",
        "df.isnull().sum()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Neo Reference ID                0\n",
              "Name                            0\n",
              "Absolute Magnitude              0\n",
              "Est Dia in KM(min)              0\n",
              "Est Dia in KM(max)              0\n",
              "Est Dia in M(min)               0\n",
              "Est Dia in M(max)               0\n",
              "Est Dia in Miles(min)           0\n",
              "Est Dia in Miles(max)           0\n",
              "Est Dia in Feet(min)            0\n",
              "Est Dia in Feet(max)            0\n",
              "Close Approach Date             0\n",
              "Epoch Date Close Approach       0\n",
              "Relative Velocity km per sec    0\n",
              "Relative Velocity km per hr     0\n",
              "Miles per hour                  0\n",
              "Miss Dist.(Astronomical)        0\n",
              "Miss Dist.(lunar)               0\n",
              "Miss Dist.(kilometers)          0\n",
              "Miss Dist.(miles)               0\n",
              "Orbiting Body                   0\n",
              "Orbit ID                        0\n",
              "Orbit Determination Date        0\n",
              "Orbit Uncertainity              0\n",
              "Minimum Orbit Intersection      0\n",
              "Jupiter Tisserand Invariant     0\n",
              "Epoch Osculation                0\n",
              "Eccentricity                    0\n",
              "Semi Major Axis                 0\n",
              "Inclination                     0\n",
              "Asc Node Longitude              0\n",
              "Orbital Period                  0\n",
              "Perihelion Distance             0\n",
              "Perihelion Arg                  0\n",
              "Aphelion Dist                   0\n",
              "Perihelion Time                 0\n",
              "Mean Anomaly                    0\n",
              "Mean Motion                     0\n",
              "Equinox                         0\n",
              "Hazardous                       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SwWZCqwrMp3y"
      },
      "source": [
        "df.drop_duplicates(inplace = True)"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d7sPN7bDWnAG",
        "outputId": "412ba51b-f384-4908-b22d-efcbbd2d124f"
      },
      "source": [
        "for col in df.columns:\n",
        "    print('Length of column'+\" \"+col+\"=\",len(df[col]))"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Length of column Neo Reference ID= 4687\n",
            "Length of column Name= 4687\n",
            "Length of column Absolute Magnitude= 4687\n",
            "Length of column Est Dia in KM(min)= 4687\n",
            "Length of column Est Dia in KM(max)= 4687\n",
            "Length of column Est Dia in M(min)= 4687\n",
            "Length of column Est Dia in M(max)= 4687\n",
            "Length of column Est Dia in Miles(min)= 4687\n",
            "Length of column Est Dia in Miles(max)= 4687\n",
            "Length of column Est Dia in Feet(min)= 4687\n",
            "Length of column Est Dia in Feet(max)= 4687\n",
            "Length of column Close Approach Date= 4687\n",
            "Length of column Epoch Date Close Approach= 4687\n",
            "Length of column Relative Velocity km per sec= 4687\n",
            "Length of column Relative Velocity km per hr= 4687\n",
            "Length of column Miles per hour= 4687\n",
            "Length of column Miss Dist.(Astronomical)= 4687\n",
            "Length of column Miss Dist.(lunar)= 4687\n",
            "Length of column Miss Dist.(kilometers)= 4687\n",
            "Length of column Miss Dist.(miles)= 4687\n",
            "Length of column Orbiting Body= 4687\n",
            "Length of column Orbit ID= 4687\n",
            "Length of column Orbit Determination Date= 4687\n",
            "Length of column Orbit Uncertainity= 4687\n",
            "Length of column Minimum Orbit Intersection= 4687\n",
            "Length of column Jupiter Tisserand Invariant= 4687\n",
            "Length of column Epoch Osculation= 4687\n",
            "Length of column Eccentricity= 4687\n",
            "Length of column Semi Major Axis= 4687\n",
            "Length of column Inclination= 4687\n",
            "Length of column Asc Node Longitude= 4687\n",
            "Length of column Orbital Period= 4687\n",
            "Length of column Perihelion Distance= 4687\n",
            "Length of column Perihelion Arg= 4687\n",
            "Length of column Aphelion Dist= 4687\n",
            "Length of column Perihelion Time= 4687\n",
            "Length of column Mean Anomaly= 4687\n",
            "Length of column Mean Motion= 4687\n",
            "Length of column Equinox= 4687\n",
            "Length of column Hazardous= 4687\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B0x-7dYW2Uxy"
      },
      "source": [
        "## Dropping the useless features"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 275
        },
        "id": "OZM_198DKwbb",
        "outputId": "b51617c6-656a-4471-d23e-f3647fe8f945"
      },
      "source": [
        "df_new = df.drop(['Neo Reference ID',\n",
        "                  'Est Dia in M(min)',\n",
        "                  'Est Dia in M(max)', \n",
        "                  'Est Dia in Miles(min)', \n",
        "                  'Est Dia in Miles(max)', \n",
        "                  'Est Dia in Feet(min)', \n",
        "                  'Est Dia in Feet(max)', \n",
        "                  'Est Dia in KM(max)',\n",
        "                  'Relative Velocity km per hr', \n",
        "                  'Miles per hour',\n",
        "                  'Miss Dist.(Astronomical)', \n",
        "                  'Miss Dist.(lunar)', \n",
        "                  'Miss Dist.(miles)',\n",
        "                  'Name',\n",
        "                  'Close Approach Date', \n",
        "                  'Epoch Date Close Approach',\n",
        "                  'Orbiting Body',\n",
        "                  'Equinox', \n",
        "                  'Orbit Determination Date',\n",
        "                  'Orbit ID',\n",
        "                  'Orbit Uncertainity'],\n",
        "                  axis=1) \n",
        "df_new.head(5)"
      ],
      "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>Absolute Magnitude</th>\n",
              "      <th>Est Dia in KM(min)</th>\n",
              "      <th>Relative Velocity km per sec</th>\n",
              "      <th>Miss Dist.(kilometers)</th>\n",
              "      <th>Minimum Orbit Intersection</th>\n",
              "      <th>Jupiter Tisserand Invariant</th>\n",
              "      <th>Epoch Osculation</th>\n",
              "      <th>Eccentricity</th>\n",
              "      <th>Semi Major Axis</th>\n",
              "      <th>Inclination</th>\n",
              "      <th>Asc Node Longitude</th>\n",
              "      <th>Orbital Period</th>\n",
              "      <th>Perihelion Distance</th>\n",
              "      <th>Perihelion Arg</th>\n",
              "      <th>Aphelion Dist</th>\n",
              "      <th>Perihelion Time</th>\n",
              "      <th>Mean Anomaly</th>\n",
              "      <th>Mean Motion</th>\n",
              "      <th>Hazardous</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>21.6</td>\n",
              "      <td>0.127220</td>\n",
              "      <td>6.115834</td>\n",
              "      <td>62753692.0</td>\n",
              "      <td>0.025282</td>\n",
              "      <td>4.634</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.425549</td>\n",
              "      <td>1.407011</td>\n",
              "      <td>6.025981</td>\n",
              "      <td>314.373913</td>\n",
              "      <td>609.599786</td>\n",
              "      <td>0.808259</td>\n",
              "      <td>57.257470</td>\n",
              "      <td>2.005764</td>\n",
              "      <td>2.458162e+06</td>\n",
              "      <td>264.837533</td>\n",
              "      <td>0.590551</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>21.3</td>\n",
              "      <td>0.146068</td>\n",
              "      <td>18.113985</td>\n",
              "      <td>57298148.0</td>\n",
              "      <td>0.186935</td>\n",
              "      <td>5.457</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.351674</td>\n",
              "      <td>1.107776</td>\n",
              "      <td>28.412996</td>\n",
              "      <td>136.717242</td>\n",
              "      <td>425.869294</td>\n",
              "      <td>0.718200</td>\n",
              "      <td>313.091975</td>\n",
              "      <td>1.497352</td>\n",
              "      <td>2.457795e+06</td>\n",
              "      <td>173.741112</td>\n",
              "      <td>0.845330</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20.3</td>\n",
              "      <td>0.231502</td>\n",
              "      <td>7.590711</td>\n",
              "      <td>7622911.5</td>\n",
              "      <td>0.043058</td>\n",
              "      <td>4.557</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.348248</td>\n",
              "      <td>1.458824</td>\n",
              "      <td>4.237961</td>\n",
              "      <td>259.475979</td>\n",
              "      <td>643.580228</td>\n",
              "      <td>0.950791</td>\n",
              "      <td>248.415038</td>\n",
              "      <td>1.966857</td>\n",
              "      <td>2.458120e+06</td>\n",
              "      <td>292.893654</td>\n",
              "      <td>0.559371</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>27.4</td>\n",
              "      <td>0.008801</td>\n",
              "      <td>11.173874</td>\n",
              "      <td>42683616.0</td>\n",
              "      <td>0.005512</td>\n",
              "      <td>5.093</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.216578</td>\n",
              "      <td>1.255903</td>\n",
              "      <td>7.905894</td>\n",
              "      <td>57.173266</td>\n",
              "      <td>514.082140</td>\n",
              "      <td>0.983902</td>\n",
              "      <td>18.707701</td>\n",
              "      <td>1.527904</td>\n",
              "      <td>2.457902e+06</td>\n",
              "      <td>68.741007</td>\n",
              "      <td>0.700277</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>21.6</td>\n",
              "      <td>0.127220</td>\n",
              "      <td>9.840831</td>\n",
              "      <td>61010824.0</td>\n",
              "      <td>0.034798</td>\n",
              "      <td>5.154</td>\n",
              "      <td>2458000.5</td>\n",
              "      <td>0.210448</td>\n",
              "      <td>1.225615</td>\n",
              "      <td>16.793382</td>\n",
              "      <td>84.629307</td>\n",
              "      <td>495.597821</td>\n",
              "      <td>0.967687</td>\n",
              "      <td>158.263596</td>\n",
              "      <td>1.483543</td>\n",
              "      <td>2.457814e+06</td>\n",
              "      <td>135.142133</td>\n",
              "      <td>0.726395</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Absolute Magnitude  Est Dia in KM(min)  ...  Mean Motion  Hazardous\n",
              "0                21.6            0.127220  ...     0.590551       True\n",
              "1                21.3            0.146068  ...     0.845330      False\n",
              "2                20.3            0.231502  ...     0.559371       True\n",
              "3                27.4            0.008801  ...     0.700277      False\n",
              "4                21.6            0.127220  ...     0.726395       True\n",
              "\n",
              "[5 rows x 19 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4YYU6j6kWI0p"
      },
      "source": [
        "## Data Visualization"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 777
        },
        "id": "ayxsBla-8ytF",
        "outputId": "4984f5e5-4b38-48b0-8949-7be96bc51272"
      },
      "source": [
        "sns.set(rc={'figure.figsize':(30,20)})\n",
        "sns.heatmap(df_new.corr(), vmin=-1, vmax=1, cmap=\"Spectral\", annot=True)\n",
        "plt.show()\n",
        "plt.close()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 2160x1440 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        },
        "id": "6eepMo0SyQ28",
        "outputId": "decfae47-d883-420f-abbb-d819558bfc84"
      },
      "source": [
        "hazardous =  df[\"Hazardous\"].value_counts()[1]\n",
        "not_hazardous = df[\"Hazardous\"].value_counts()[0]\n",
        "plt.figure(figsize=(5,5))\n",
        "plt.pie(df[\"Hazardous\"].value_counts().values,labels=['not_hazardous','hazardous'], autopct=\"%1.0f%%\")\n",
        "plt.title(\"Proportion of hazardous asteroids in dataset\")\n",
        "plt.show()\n",
        "print(\"There are \" + str(hazardous) + \"  potential asteroids that can collide \" \n",
        "      + \"and \" + str(not_hazardous) + \" that might miss the collision .\")"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "There are 755  potential asteroids that can collide and 3932 that might miss the collision .\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 752
        },
        "id": "I0lwkSTO1lyb",
        "outputId": "ce97f0b5-bf50-4533-d80c-4fd6d3acd8ad"
      },
      "source": [
        "sns.countplot(df['Hazardous'])"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f301c29a590>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 2160x1440 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kOM68UOUWMJA"
      },
      "source": [
        "## Assigning Features and Labels"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z6PwEAlJ9W3j",
        "outputId": "ba9762e4-9e75-46da-d3cc-d6f2a03bfcf1"
      },
      "source": [
        "y = df_new.iloc[:,-1].values\n",
        "y.shape"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4687,)"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "icu7hA3hZOKd",
        "outputId": "fbfc38d1-bac3-4f39-c1f0-87b861eb14a1"
      },
      "source": [
        "X = df_new.iloc[:,:-1].values\n",
        "X.shape\n"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4687, 18)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ubTA-LQC2wtH"
      },
      "source": [
        "## Categorical Encoding"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GExDxDQqumW-",
        "outputId": "1d962cbe-566f-41dc-f224-6fd8d127016d"
      },
      "source": [
        "le = LabelEncoder()\n",
        "y = le.fit_transform(y)\n",
        "print(y)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[1 0 1 ... 0 0 0]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Lf99RoOiWF4C"
      },
      "source": [
        "## Train Test Split"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fXiOI1XRfSKt"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "X_train ,X_test, y_train, y_test = train_test_split(X,y,test_size = 0.2,random_state = 0)"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jbobvtYwWDAV"
      },
      "source": [
        "## Feature Scaling"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z-kk-CKbfCL9"
      },
      "source": [
        "from sklearn.preprocessing import StandardScaler\n",
        "sc = StandardScaler()\n",
        "X_train = sc.fit_transform(X_train)\n",
        "X_test = sc.transform(X_test)\n"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6f1CyJ6jVmEr"
      },
      "source": [
        "## XGB Classifier"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fyTN9G8K6abj"
      },
      "source": [
        "classifier = XGBClassifier()\n",
        "classifier.fit(X_train,y_train)\n",
        "y_pred = classifier.predict(X_test)"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q2-v6ISw6j5F",
        "outputId": "2a86ecc4-4e3d-473a-84f9-4db73a6da73f"
      },
      "source": [
        "accuracy = accuracy_score(y_test,y_pred)\n",
        "print('The accuracy of XGB Model is: {} %'.format(accuracy*100))"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The accuracy of XGB Model is: 99.36034115138592 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 715
        },
        "id": "WHJmsLwHqY28",
        "outputId": "a6780ffa-bfff-4bde-a245-9b9548e77cd1"
      },
      "source": [
        "cm = confusion_matrix(y_test, y_pred)\n",
        "sns.heatmap(cm,\n",
        "            annot=True,\n",
        "            cbar=False,\n",
        "            cmap = 'YlGnBu', \n",
        "            linecolor= 'yellow' , \n",
        "            linewidths= '10',\n",
        "            annot_kws={'size': 50})\n",
        "plt.ylabel('True Label',fontsize = 40)\n",
        "plt.xlabel('Predicted Label',fontsize = 40)\n",
        "plt.title('Confusion Matrix',fontsize = 40)\n",
        "plt.show()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 2160x1440 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "41JFvwIKj9BI",
        "outputId": "cca7778a-f3ad-4dc7-aed1-7678f1b63e4e"
      },
      "source": [
        "report = classification_report(y_test, y_pred)\n",
        "print('The Classification report is as follows:\\n\\n{}'.format(report))"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The Classification report is as follows:\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.99      1.00      1.00       793\n",
            "           1       0.99      0.97      0.98       145\n",
            "\n",
            "    accuracy                           0.99       938\n",
            "   macro avg       0.99      0.98      0.99       938\n",
            "weighted avg       0.99      0.99      0.99       938\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eDgXO0hLqySs",
        "outputId": "e7c1a841-7bea-466b-e5a1-f18d4564aed7"
      },
      "source": [
        "accuracies = cross_val_score(estimator = classifier, \n",
        "                             X = X_train, \n",
        "                             y = y_train, \n",
        "                             cv = 10)\n",
        "print(\"Accuracy of k-Fold Cross Validation is: {}%\".format(accuracies.mean()*100))"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of k-Fold Cross Validation is: 99.54645276292335%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ssh4q_tHYgAA"
      },
      "source": [
        "## Gradient Boost Classifier"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MZ7rTWm3Yl08"
      },
      "source": [
        "classifier = GradientBoostingClassifier(loss='deviance',\n",
        "                                        learning_rate=0.1,\n",
        "                                        n_estimators=100)\n",
        "classifier.fit(X_train,y_train)\n",
        "y_pred = classifier.predict(X_test)"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6bHVExYwYy2D",
        "outputId": "7b68fe93-c2e5-4ad4-d7e8-a4953520b5f4"
      },
      "source": [
        "accuracy = accuracy_score(y_test,y_pred)\n",
        "print('The accuracy of Gradient Boost Classifier Model is: {} %'.format(accuracy*100))"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The accuracy of Gradient Boost Classifier Model is: 99.36034115138592 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 715
        },
        "id": "tSEOeKZPkApv",
        "outputId": "565f1bbd-a674-4189-c70c-2864236c469b"
      },
      "source": [
        "cm = confusion_matrix(y_test, y_pred)\n",
        "sns.heatmap(cm,\n",
        "            annot=True,\n",
        "            cbar=False,\n",
        "            cmap = 'Dark2_r', \n",
        "            linecolor= 'grey' , \n",
        "            linewidths= '10',\n",
        "            annot_kws={'size': 50})\n",
        "plt.ylabel('True Label',fontsize = 40)\n",
        "plt.xlabel('Predicted Label',fontsize = 40)\n",
        "plt.title('Confusion Matrix',fontsize = 40)\n",
        "plt.show()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 2160x1440 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DrG4KkZvj7b5",
        "outputId": "2c4bc1c0-9809-4126-93c2-04fb19229949"
      },
      "source": [
        "report = classification_report(y_test, y_pred)\n",
        "print('The Classification report is as follows:\\n\\n{}'.format(report))"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The Classification report is as follows:\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.99      1.00      1.00       793\n",
            "           1       1.00      0.96      0.98       145\n",
            "\n",
            "    accuracy                           0.99       938\n",
            "   macro avg       1.00      0.98      0.99       938\n",
            "weighted avg       0.99      0.99      0.99       938\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oW8K4JHhsm1C",
        "outputId": "566e4028-738a-45b2-e2d6-dc54ad3ca223"
      },
      "source": [
        "accuracies = cross_val_score(estimator = classifier, \n",
        "                             X = X_train, \n",
        "                             y = y_train, \n",
        "                             cv = 10)\n",
        "print(\"Accuracy of k-Fold Cross Validation is: {}%\".format(accuracies.mean()*100))"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of k-Fold Cross Validation is: 99.51985739750444%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E6A8oYXCVsVl"
      },
      "source": [
        "## Ada Boost Classifier"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xIgoHcWA-KBO"
      },
      "source": [
        "classifier = AdaBoostClassifier()\n",
        "classifier.fit(X_train,y_train)\n",
        "y_pred = classifier.predict(X_test)"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kHMCXWdj-UTb",
        "outputId": "c07c750a-4d11-41e8-a26a-ed40ddf924e9"
      },
      "source": [
        "accuracy = accuracy_score(y_test,y_pred)\n",
        "print('The accuracy of Ada Boost Classifier Model is: {} %'.format(accuracy*100))"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The accuracy of Ada Boost Classifier Model is: 99.46695095948827 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 715
        },
        "id": "T8R0r6CdjtcD",
        "outputId": "9de5a3fd-8586-4f05-9445-fe4858658876"
      },
      "source": [
        "cm = confusion_matrix(y_test, y_pred)\n",
        "sns.heatmap(cm,\n",
        "            annot=True,\n",
        "            cbar=False,\n",
        "            cmap = 'gist_ncar', \n",
        "            linecolor= 'violet' , \n",
        "            linewidths= '10',\n",
        "            annot_kws={'size': 50})\n",
        "plt.ylabel('True Label',fontsize = 40)\n",
        "plt.xlabel('Predicted Label',fontsize = 40)\n",
        "plt.title('Confusion Matrix',fontsize = 40)\n",
        "plt.show()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 2160x1440 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-aPEb4KEjsjl",
        "outputId": "05450cc1-5501-4f1d-fda4-eda08efd77af"
      },
      "source": [
        "report = classification_report(y_test, y_pred)\n",
        "print('The Classification report is as follows:\\n\\n{}'.format(report))"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The Classification report is as follows:\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.99      1.00      1.00       793\n",
            "           1       1.00      0.97      0.98       145\n",
            "\n",
            "    accuracy                           0.99       938\n",
            "   macro avg       1.00      0.98      0.99       938\n",
            "weighted avg       0.99      0.99      0.99       938\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U4Wp0PUMsuvr",
        "outputId": "3208b4f1-ec14-434e-dc72-4b024776a2a5"
      },
      "source": [
        "accuracies = cross_val_score(estimator = classifier, \n",
        "                             X = X_train, \n",
        "                             y = y_train, \n",
        "                             cv = 10)\n",
        "print(\"Accuracy of k-Fold Cross Validation is: {}%\".format(accuracies.mean()*100))"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of k-Fold Cross Validation is: 99.5731907308378%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yVh9Cxv1VZ2Y"
      },
      "source": [
        "## Random Forest"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sshLWQMiT_4J"
      },
      "source": [
        "classifier = RandomForestClassifier(n_estimators = 10, \n",
        "                                    criterion = 'entropy', \n",
        "                                    random_state = 0)\n",
        "classifier.fit(X_train, y_train)\n",
        "y_pred = classifier.predict(X_test)\n"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xrz2ErT3ULjH",
        "outputId": "22e47049-1ec5-4af1-e012-dce7d6926bba"
      },
      "source": [
        "accuracy = accuracy_score(y_test,y_pred)\n",
        "print('The accuracy of Random Forest Classifier Model is: {} %'.format(accuracy*100))"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The accuracy of Random Forest Classifier Model is: 99.36034115138592 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "VPPEp4CXgzPb",
        "outputId": "e59c9a5a-1a42-4a11-f8c0-671e92319334"
      },
      "source": [
        "cm = confusion_matrix(y_test, y_pred)\n",
        "sns.heatmap(cm,\n",
        "            annot=True,\n",
        "            cbar=False,\n",
        "            cmap = 'plasma_r', \n",
        "            linecolor= 'orange' , \n",
        "            linewidths= '10',\n",
        "            annot_kws={'size': 50})\n",
        "plt.ylabel('True Label',fontsize = 40)\n",
        "plt.xlabel('Predicted Label',fontsize = 40)\n",
        "plt.title('Confusion Matrix',fontsize = 40)\n",
        "plt.show()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 2160x1440 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uytGJVvMg7qC",
        "outputId": "988a69d3-9914-45f1-a875-5fce217df307"
      },
      "source": [
        "report = classification_report(y_test, y_pred)\n",
        "print('The Classification report is as follows:\\n\\n{}'.format(report))"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The Classification report is as follows:\n",
            "\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.99      1.00      1.00       793\n",
            "           1       1.00      0.96      0.98       145\n",
            "\n",
            "    accuracy                           0.99       938\n",
            "   macro avg       1.00      0.98      0.99       938\n",
            "weighted avg       0.99      0.99      0.99       938\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X83VyHMjtBG1",
        "outputId": "a940b286-fb92-4cc2-fd0e-0254f8c114ae"
      },
      "source": [
        "accuracies = cross_val_score(estimator = classifier, \n",
        "                             X = X_train, \n",
        "                             y = y_train, \n",
        "                             cv = 10)\n",
        "print(\"Accuracy of k-Fold Cross Validation is: {}%\".format(accuracies.mean()*100))"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of k-Fold Cross Validation is: 99.5731907308378%\n"
          ]
        }
      ]
    }
  ]
}