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+++ b/Lung_Cancer_Prediction.ipynb
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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Lung_Cancer_Prediction.ipynb",
+      "provenance": [],
+      "collapsed_sections": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "62y1lAc6G-C5"
+      },
+      "source": [
+        "#Lung Cancer Prediction Using Machine Learning"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "f9crsy0QHK6Z"
+      },
+      "source": [
+        "##Importing various Libraries"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "xkomKUJQHXSS"
+      },
+      "source": [
+        "\n",
+        "import pandas as pd\n",
+        "import matplotlib.pyplot as plt\n",
+        "import seaborn as sns\n"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "uTxEpPXeHaDx"
+      },
+      "source": [
+        "##Data Description\n",
+        "Using the read excel function from pandas to load the dataset."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "resources": {
+            "http://localhost:8080/nbextensions/google.colab/files.js": {
+              "data": 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",
+              "ok": true,
+              "headers": [
+                [
+                  "content-type",
+                  "application/javascript"
+                ]
+              ],
+              "status": 200,
+              "status_text": ""
+            }
+          },
+          "base_uri": "https://localhost:8080/",
+          "height": 72
+        },
+        "id": "RdwFWKgnUjOi",
+        "outputId": "98d2f6a9-6bd7-4bf5-d386-caa58bff8d11"
+      },
+      "source": [
+        "#from google.colab import files\n",
+        "#uploaded = files.upload()"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/html": [
+              "\n",
+              "     <input type=\"file\" id=\"files-319f04d9-06b1-4b75-8614-188675d05068\" name=\"files[]\" multiple disabled\n",
+              "        style=\"border:none\" />\n",
+              "     <output id=\"result-319f04d9-06b1-4b75-8614-188675d05068\">\n",
+              "      Upload widget is only available when the cell has been executed in the\n",
+              "      current browser session. Please rerun this cell to enable.\n",
+              "      </output>\n",
+              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
+            ],
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        },
+        {
+          "output_type": "stream",
+          "text": [
+            "Saving datasets.xlsx to datasets.xlsx\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "aVAabDGuHfn5"
+      },
+      "source": [
+        "data = pd.read_excel(\"datasets.xlsx\")"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "w_0Y7oCPHmE5"
+      },
+      "source": [
+        "Using various functions to take a insight on data."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 275
+        },
+        "id": "wsxleaW-Ho9w",
+        "outputId": "ad00bcb1-dc9c-4c99-801a-a34fe7f9d9a7"
+      },
+      "source": [
+        "data.head()"
+      ],
+      "execution_count": null,
+      "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>Patient Id</th>\n",
+              "      <th>Age</th>\n",
+              "      <th>Gender</th>\n",
+              "      <th>Air Pollution</th>\n",
+              "      <th>Alcohol use</th>\n",
+              "      <th>Dust Allergy</th>\n",
+              "      <th>OccuPational Hazards</th>\n",
+              "      <th>Genetic Risk</th>\n",
+              "      <th>chronic Lung Disease</th>\n",
+              "      <th>Balanced Diet</th>\n",
+              "      <th>Obesity</th>\n",
+              "      <th>Smoking</th>\n",
+              "      <th>Passive Smoker</th>\n",
+              "      <th>Chest Pain</th>\n",
+              "      <th>Coughing of Blood</th>\n",
+              "      <th>Fatigue</th>\n",
+              "      <th>Weight Loss</th>\n",
+              "      <th>Shortness of Breath</th>\n",
+              "      <th>Wheezing</th>\n",
+              "      <th>Swallowing Difficulty</th>\n",
+              "      <th>Clubbing of Finger Nails</th>\n",
+              "      <th>Frequent Cold</th>\n",
+              "      <th>Dry Cough</th>\n",
+              "      <th>Snoring</th>\n",
+              "      <th>Level</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>P1</td>\n",
+              "      <td>33</td>\n",
+              "      <td>1</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>5</td>\n",
+              "      <td>4</td>\n",
+              "      <td>3</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>3</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>Low</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>P10</td>\n",
+              "      <td>17</td>\n",
+              "      <td>1</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>5</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>3</td>\n",
+              "      <td>7</td>\n",
+              "      <td>8</td>\n",
+              "      <td>6</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "      <td>7</td>\n",
+              "      <td>2</td>\n",
+              "      <td>Medium</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>P100</td>\n",
+              "      <td>35</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>5</td>\n",
+              "      <td>6</td>\n",
+              "      <td>5</td>\n",
+              "      <td>5</td>\n",
+              "      <td>4</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8</td>\n",
+              "      <td>8</td>\n",
+              "      <td>7</td>\n",
+              "      <td>9</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>2</td>\n",
+              "      <td>High</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>P1000</td>\n",
+              "      <td>37</td>\n",
+              "      <td>1</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>8</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>5</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>5</td>\n",
+              "      <td>High</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>P101</td>\n",
+              "      <td>46</td>\n",
+              "      <td>1</td>\n",
+              "      <td>6</td>\n",
+              "      <td>8</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>8</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>9</td>\n",
+              "      <td>3</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>High</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "  Patient Id  Age  Gender  ...  Dry Cough  Snoring   Level\n",
+              "0         P1   33       1  ...          3        4     Low\n",
+              "1        P10   17       1  ...          7        2  Medium\n",
+              "2       P100   35       1  ...          7        2    High\n",
+              "3      P1000   37       1  ...          7        5    High\n",
+              "4       P101   46       1  ...          2        3    High\n",
+              "\n",
+              "[5 rows x 25 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 4
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Q0YfUMi2Wezm",
+        "outputId": "f1735ed5-23e6-4e28-9e75-62b0d353f0f9"
+      },
+      "source": [
+        "data.shape"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(1000, 25)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 5
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "UYtTyp1IWnE7",
+        "outputId": "971e064f-9931-46fd-b6a4-c0ef9dfc402e"
+      },
+      "source": [
+        "data.info()"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "<class 'pandas.core.frame.DataFrame'>\n",
+            "RangeIndex: 1000 entries, 0 to 999\n",
+            "Data columns (total 25 columns):\n",
+            " #   Column                    Non-Null Count  Dtype \n",
+            "---  ------                    --------------  ----- \n",
+            " 0   Patient Id                1000 non-null   object\n",
+            " 1   Age                       1000 non-null   int64 \n",
+            " 2   Gender                    1000 non-null   int64 \n",
+            " 3   Air Pollution             1000 non-null   int64 \n",
+            " 4   Alcohol use               1000 non-null   int64 \n",
+            " 5   Dust Allergy              1000 non-null   int64 \n",
+            " 6   OccuPational Hazards      1000 non-null   int64 \n",
+            " 7   Genetic Risk              1000 non-null   int64 \n",
+            " 8   chronic Lung Disease      1000 non-null   int64 \n",
+            " 9   Balanced Diet             1000 non-null   int64 \n",
+            " 10  Obesity                   1000 non-null   int64 \n",
+            " 11  Smoking                   1000 non-null   int64 \n",
+            " 12  Passive Smoker            1000 non-null   int64 \n",
+            " 13  Chest Pain                1000 non-null   int64 \n",
+            " 14  Coughing of Blood         1000 non-null   int64 \n",
+            " 15  Fatigue                   1000 non-null   int64 \n",
+            " 16  Weight Loss               1000 non-null   int64 \n",
+            " 17  Shortness of Breath       1000 non-null   int64 \n",
+            " 18  Wheezing                  1000 non-null   int64 \n",
+            " 19  Swallowing Difficulty     1000 non-null   int64 \n",
+            " 20  Clubbing of Finger Nails  1000 non-null   int64 \n",
+            " 21  Frequent Cold             1000 non-null   int64 \n",
+            " 22  Dry Cough                 1000 non-null   int64 \n",
+            " 23  Snoring                   1000 non-null   int64 \n",
+            " 24  Level                     1000 non-null   object\n",
+            "dtypes: int64(23), object(2)\n",
+            "memory usage: 195.4+ KB\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 351
+        },
+        "id": "fO9jc2wxWqDp",
+        "outputId": "33ec8c8b-8afe-45b7-8aa6-c64eb0f2f1cf"
+      },
+      "source": [
+        "data.describe()"
+      ],
+      "execution_count": null,
+      "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>Gender</th>\n",
+              "      <th>Air Pollution</th>\n",
+              "      <th>Alcohol use</th>\n",
+              "      <th>Dust Allergy</th>\n",
+              "      <th>OccuPational Hazards</th>\n",
+              "      <th>Genetic Risk</th>\n",
+              "      <th>chronic Lung Disease</th>\n",
+              "      <th>Balanced Diet</th>\n",
+              "      <th>Obesity</th>\n",
+              "      <th>Smoking</th>\n",
+              "      <th>Passive Smoker</th>\n",
+              "      <th>Chest Pain</th>\n",
+              "      <th>Coughing of Blood</th>\n",
+              "      <th>Fatigue</th>\n",
+              "      <th>Weight Loss</th>\n",
+              "      <th>Shortness of Breath</th>\n",
+              "      <th>Wheezing</th>\n",
+              "      <th>Swallowing Difficulty</th>\n",
+              "      <th>Clubbing of Finger Nails</th>\n",
+              "      <th>Frequent Cold</th>\n",
+              "      <th>Dry Cough</th>\n",
+              "      <th>Snoring</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.0000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>mean</th>\n",
+              "      <td>37.174000</td>\n",
+              "      <td>1.402000</td>\n",
+              "      <td>3.8400</td>\n",
+              "      <td>4.563000</td>\n",
+              "      <td>5.165000</td>\n",
+              "      <td>4.840000</td>\n",
+              "      <td>4.580000</td>\n",
+              "      <td>4.380000</td>\n",
+              "      <td>4.491000</td>\n",
+              "      <td>4.465000</td>\n",
+              "      <td>3.948000</td>\n",
+              "      <td>4.195000</td>\n",
+              "      <td>4.438000</td>\n",
+              "      <td>4.859000</td>\n",
+              "      <td>3.856000</td>\n",
+              "      <td>3.855000</td>\n",
+              "      <td>4.240000</td>\n",
+              "      <td>3.777000</td>\n",
+              "      <td>3.746000</td>\n",
+              "      <td>3.923000</td>\n",
+              "      <td>3.536000</td>\n",
+              "      <td>3.853000</td>\n",
+              "      <td>2.926000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>std</th>\n",
+              "      <td>12.005493</td>\n",
+              "      <td>0.490547</td>\n",
+              "      <td>2.0304</td>\n",
+              "      <td>2.620477</td>\n",
+              "      <td>1.980833</td>\n",
+              "      <td>2.107805</td>\n",
+              "      <td>2.126999</td>\n",
+              "      <td>1.848518</td>\n",
+              "      <td>2.135528</td>\n",
+              "      <td>2.124921</td>\n",
+              "      <td>2.495902</td>\n",
+              "      <td>2.311778</td>\n",
+              "      <td>2.280209</td>\n",
+              "      <td>2.427965</td>\n",
+              "      <td>2.244616</td>\n",
+              "      <td>2.206546</td>\n",
+              "      <td>2.285087</td>\n",
+              "      <td>2.041921</td>\n",
+              "      <td>2.270383</td>\n",
+              "      <td>2.388048</td>\n",
+              "      <td>1.832502</td>\n",
+              "      <td>2.039007</td>\n",
+              "      <td>1.474686</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>min</th>\n",
+              "      <td>14.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.0000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25%</th>\n",
+              "      <td>27.750000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>2.0000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>50%</th>\n",
+              "      <td>36.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>3.0000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>75%</th>\n",
+              "      <td>45.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>6.0000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>max</th>\n",
+              "      <td>73.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>8.0000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "               Age       Gender  ...    Dry Cough      Snoring\n",
+              "count  1000.000000  1000.000000  ...  1000.000000  1000.000000\n",
+              "mean     37.174000     1.402000  ...     3.853000     2.926000\n",
+              "std      12.005493     0.490547  ...     2.039007     1.474686\n",
+              "min      14.000000     1.000000  ...     1.000000     1.000000\n",
+              "25%      27.750000     1.000000  ...     2.000000     2.000000\n",
+              "50%      36.000000     1.000000  ...     4.000000     3.000000\n",
+              "75%      45.000000     2.000000  ...     6.000000     4.000000\n",
+              "max      73.000000     2.000000  ...     7.000000     7.000000\n",
+              "\n",
+              "[8 rows x 23 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 7
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 444
+        },
+        "id": "3YjoKs3WWvRo",
+        "outputId": "139851b0-583c-49c9-b647-40b0794e37a2"
+      },
+      "source": [
+        "data.describe(include=\"all\")"
+      ],
+      "execution_count": null,
+      "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>Patient Id</th>\n",
+              "      <th>Age</th>\n",
+              "      <th>Gender</th>\n",
+              "      <th>Air Pollution</th>\n",
+              "      <th>Alcohol use</th>\n",
+              "      <th>Dust Allergy</th>\n",
+              "      <th>OccuPational Hazards</th>\n",
+              "      <th>Genetic Risk</th>\n",
+              "      <th>chronic Lung Disease</th>\n",
+              "      <th>Balanced Diet</th>\n",
+              "      <th>Obesity</th>\n",
+              "      <th>Smoking</th>\n",
+              "      <th>Passive Smoker</th>\n",
+              "      <th>Chest Pain</th>\n",
+              "      <th>Coughing of Blood</th>\n",
+              "      <th>Fatigue</th>\n",
+              "      <th>Weight Loss</th>\n",
+              "      <th>Shortness of Breath</th>\n",
+              "      <th>Wheezing</th>\n",
+              "      <th>Swallowing Difficulty</th>\n",
+              "      <th>Clubbing of Finger Nails</th>\n",
+              "      <th>Frequent Cold</th>\n",
+              "      <th>Dry Cough</th>\n",
+              "      <th>Snoring</th>\n",
+              "      <th>Level</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>1000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.0000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000.000000</td>\n",
+              "      <td>1000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>unique</th>\n",
+              "      <td>1000</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>3</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>top</th>\n",
+              "      <td>P325</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>High</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>freq</th>\n",
+              "      <td>1</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>365</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>mean</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>37.174000</td>\n",
+              "      <td>1.402000</td>\n",
+              "      <td>3.8400</td>\n",
+              "      <td>4.563000</td>\n",
+              "      <td>5.165000</td>\n",
+              "      <td>4.840000</td>\n",
+              "      <td>4.580000</td>\n",
+              "      <td>4.380000</td>\n",
+              "      <td>4.491000</td>\n",
+              "      <td>4.465000</td>\n",
+              "      <td>3.948000</td>\n",
+              "      <td>4.195000</td>\n",
+              "      <td>4.438000</td>\n",
+              "      <td>4.859000</td>\n",
+              "      <td>3.856000</td>\n",
+              "      <td>3.855000</td>\n",
+              "      <td>4.240000</td>\n",
+              "      <td>3.777000</td>\n",
+              "      <td>3.746000</td>\n",
+              "      <td>3.923000</td>\n",
+              "      <td>3.536000</td>\n",
+              "      <td>3.853000</td>\n",
+              "      <td>2.926000</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>std</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>12.005493</td>\n",
+              "      <td>0.490547</td>\n",
+              "      <td>2.0304</td>\n",
+              "      <td>2.620477</td>\n",
+              "      <td>1.980833</td>\n",
+              "      <td>2.107805</td>\n",
+              "      <td>2.126999</td>\n",
+              "      <td>1.848518</td>\n",
+              "      <td>2.135528</td>\n",
+              "      <td>2.124921</td>\n",
+              "      <td>2.495902</td>\n",
+              "      <td>2.311778</td>\n",
+              "      <td>2.280209</td>\n",
+              "      <td>2.427965</td>\n",
+              "      <td>2.244616</td>\n",
+              "      <td>2.206546</td>\n",
+              "      <td>2.285087</td>\n",
+              "      <td>2.041921</td>\n",
+              "      <td>2.270383</td>\n",
+              "      <td>2.388048</td>\n",
+              "      <td>1.832502</td>\n",
+              "      <td>2.039007</td>\n",
+              "      <td>1.474686</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>min</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>14.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.0000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25%</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>27.750000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>2.0000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>50%</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>36.000000</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>3.0000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>3.000000</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>75%</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>45.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>6.0000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>5.000000</td>\n",
+              "      <td>6.000000</td>\n",
+              "      <td>4.000000</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>max</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>73.000000</td>\n",
+              "      <td>2.000000</td>\n",
+              "      <td>8.0000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>8.000000</td>\n",
+              "      <td>9.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>7.000000</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "       Patient Id          Age       Gender  ...    Dry Cough      Snoring  Level\n",
+              "count        1000  1000.000000  1000.000000  ...  1000.000000  1000.000000   1000\n",
+              "unique       1000          NaN          NaN  ...          NaN          NaN      3\n",
+              "top          P325          NaN          NaN  ...          NaN          NaN   High\n",
+              "freq            1          NaN          NaN  ...          NaN          NaN    365\n",
+              "mean          NaN    37.174000     1.402000  ...     3.853000     2.926000    NaN\n",
+              "std           NaN    12.005493     0.490547  ...     2.039007     1.474686    NaN\n",
+              "min           NaN    14.000000     1.000000  ...     1.000000     1.000000    NaN\n",
+              "25%           NaN    27.750000     1.000000  ...     2.000000     2.000000    NaN\n",
+              "50%           NaN    36.000000     1.000000  ...     4.000000     3.000000    NaN\n",
+              "75%           NaN    45.000000     2.000000  ...     6.000000     4.000000    NaN\n",
+              "max           NaN    73.000000     2.000000  ...     7.000000     7.000000    NaN\n",
+              "\n",
+              "[11 rows x 25 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 8
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CQaEgKg3W14o"
+      },
+      "source": [
+        "\n",
+        "There are 1000 Rows and 25 Columns : \n",
+        "\n",
+        "24 Columns contribute the X values and 25th is the \"Level\" column which tells \n",
+        "us about the cancer. \n",
+        "\n",
+        "Patient Id  \n",
+        "Age  \n",
+        "Gender  \n",
+        "Air Pollution \n",
+        "Alcohol use  \n",
+        "Dust Allergy  \n",
+        "OccuPational Hazards  \n",
+        "Genetic Risk  \n",
+        "chronic Lung Disease  \n",
+        "Balanced Diet  \n",
+        "Obesity\n",
+        "Smoking  \n",
+        "Passive Smoker  \n",
+        "Chest Pain  \n",
+        "Coughing of Blood  \n",
+        "Fatigue\n",
+        "Weight Loss  \n",
+        "Shortness of Breath  \n",
+        "Wheezing  \n",
+        "Swallowing Difficulty\n",
+        "Clubbing of Finger Nails  \n",
+        "Frequent Cold  \n",
+        "Dry Cough  \n",
+        "Snoring   \n",
+        "Level\n",
+        "\n",
+        "Every column is numeric except level which can be converted.\n",
+        "\n",
+        "Also every column is complete that is there is no missing data.\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Jsx9f7b1XGXr"
+      },
+      "source": [
+        "##Data Analysis and Visualization"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "B4LXle2MWzUp"
+      },
+      "source": [
+        "#Changing the 'Level' column to numeric.\n",
+        "level_mapping = {\"Low\": 1, \"Medium\": 2, \"High\": 3}\n",
+        "data[\"Level\"] = data[\"Level\"].map(level_mapping)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Vh0PIo00XOp8"
+      },
+      "source": [
+        "# Dropping the Patient Id as it gives no useful information.\n",
+        "data.drop(\"Patient Id\", axis=1, inplace=True)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 275
+        },
+        "id": "178hAe17XTws",
+        "outputId": "3ad4bce0-1e86-4aa3-fafc-0916f4df462f"
+      },
+      "source": [
+        "data.head()"
+      ],
+      "execution_count": null,
+      "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>Gender</th>\n",
+              "      <th>Air Pollution</th>\n",
+              "      <th>Alcohol use</th>\n",
+              "      <th>Dust Allergy</th>\n",
+              "      <th>OccuPational Hazards</th>\n",
+              "      <th>Genetic Risk</th>\n",
+              "      <th>chronic Lung Disease</th>\n",
+              "      <th>Balanced Diet</th>\n",
+              "      <th>Obesity</th>\n",
+              "      <th>Smoking</th>\n",
+              "      <th>Passive Smoker</th>\n",
+              "      <th>Chest Pain</th>\n",
+              "      <th>Coughing of Blood</th>\n",
+              "      <th>Fatigue</th>\n",
+              "      <th>Weight Loss</th>\n",
+              "      <th>Shortness of Breath</th>\n",
+              "      <th>Wheezing</th>\n",
+              "      <th>Swallowing Difficulty</th>\n",
+              "      <th>Clubbing of Finger Nails</th>\n",
+              "      <th>Frequent Cold</th>\n",
+              "      <th>Dry Cough</th>\n",
+              "      <th>Snoring</th>\n",
+              "      <th>Level</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>33</td>\n",
+              "      <td>1</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>5</td>\n",
+              "      <td>4</td>\n",
+              "      <td>3</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>3</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>1</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>17</td>\n",
+              "      <td>1</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>5</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>3</td>\n",
+              "      <td>7</td>\n",
+              "      <td>8</td>\n",
+              "      <td>6</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "      <td>7</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>35</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>5</td>\n",
+              "      <td>6</td>\n",
+              "      <td>5</td>\n",
+              "      <td>5</td>\n",
+              "      <td>4</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4</td>\n",
+              "      <td>8</td>\n",
+              "      <td>8</td>\n",
+              "      <td>7</td>\n",
+              "      <td>9</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>37</td>\n",
+              "      <td>1</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>8</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>5</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>5</td>\n",
+              "      <td>3</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>46</td>\n",
+              "      <td>1</td>\n",
+              "      <td>6</td>\n",
+              "      <td>8</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>6</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>8</td>\n",
+              "      <td>7</td>\n",
+              "      <td>7</td>\n",
+              "      <td>9</td>\n",
+              "      <td>3</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>3</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   Age  Gender  Air Pollution  ...  Dry Cough  Snoring  Level\n",
+              "0   33       1              2  ...          3        4      1\n",
+              "1   17       1              3  ...          7        2      2\n",
+              "2   35       1              4  ...          7        2      3\n",
+              "3   37       1              7  ...          7        5      3\n",
+              "4   46       1              6  ...          2        3      3\n",
+              "\n",
+              "[5 rows x 24 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 11
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "svsYpuySXida",
+        "outputId": "6fbd827b-4beb-4cc4-b707-0a691a464f91"
+      },
+      "source": [
+        "# Correlation values:\n",
+        "data.corr()"
+      ],
+      "execution_count": null,
+      "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>Gender</th>\n",
+              "      <th>Air Pollution</th>\n",
+              "      <th>Alcohol use</th>\n",
+              "      <th>Dust Allergy</th>\n",
+              "      <th>OccuPational Hazards</th>\n",
+              "      <th>Genetic Risk</th>\n",
+              "      <th>chronic Lung Disease</th>\n",
+              "      <th>Balanced Diet</th>\n",
+              "      <th>Obesity</th>\n",
+              "      <th>Smoking</th>\n",
+              "      <th>Passive Smoker</th>\n",
+              "      <th>Chest Pain</th>\n",
+              "      <th>Coughing of Blood</th>\n",
+              "      <th>Fatigue</th>\n",
+              "      <th>Weight Loss</th>\n",
+              "      <th>Shortness of Breath</th>\n",
+              "      <th>Wheezing</th>\n",
+              "      <th>Swallowing Difficulty</th>\n",
+              "      <th>Clubbing of Finger Nails</th>\n",
+              "      <th>Frequent Cold</th>\n",
+              "      <th>Dry Cough</th>\n",
+              "      <th>Snoring</th>\n",
+              "      <th>Level</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>Age</th>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>-0.202086</td>\n",
+              "      <td>0.099494</td>\n",
+              "      <td>0.151742</td>\n",
+              "      <td>0.035202</td>\n",
+              "      <td>0.062177</td>\n",
+              "      <td>0.073151</td>\n",
+              "      <td>0.128952</td>\n",
+              "      <td>0.004863</td>\n",
+              "      <td>0.034337</td>\n",
+              "      <td>0.075333</td>\n",
+              "      <td>0.004908</td>\n",
+              "      <td>0.012864</td>\n",
+              "      <td>0.053006</td>\n",
+              "      <td>0.095059</td>\n",
+              "      <td>0.106946</td>\n",
+              "      <td>0.035329</td>\n",
+              "      <td>-0.095354</td>\n",
+              "      <td>-0.105833</td>\n",
+              "      <td>0.039258</td>\n",
+              "      <td>-0.012706</td>\n",
+              "      <td>0.012128</td>\n",
+              "      <td>-0.004700</td>\n",
+              "      <td>0.060048</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Gender</th>\n",
+              "      <td>-0.202086</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>-0.246912</td>\n",
+              "      <td>-0.227636</td>\n",
+              "      <td>-0.204312</td>\n",
+              "      <td>-0.192343</td>\n",
+              "      <td>-0.222727</td>\n",
+              "      <td>-0.205061</td>\n",
+              "      <td>-0.099741</td>\n",
+              "      <td>-0.123813</td>\n",
+              "      <td>-0.206924</td>\n",
+              "      <td>-0.184826</td>\n",
+              "      <td>-0.218426</td>\n",
+              "      <td>-0.146505</td>\n",
+              "      <td>-0.116467</td>\n",
+              "      <td>-0.057993</td>\n",
+              "      <td>-0.045972</td>\n",
+              "      <td>-0.076304</td>\n",
+              "      <td>-0.058324</td>\n",
+              "      <td>-0.034219</td>\n",
+              "      <td>-0.000526</td>\n",
+              "      <td>-0.123001</td>\n",
+              "      <td>-0.181618</td>\n",
+              "      <td>-0.164985</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Air Pollution</th>\n",
+              "      <td>0.099494</td>\n",
+              "      <td>-0.246912</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.747293</td>\n",
+              "      <td>0.637503</td>\n",
+              "      <td>0.608924</td>\n",
+              "      <td>0.705276</td>\n",
+              "      <td>0.626701</td>\n",
+              "      <td>0.524873</td>\n",
+              "      <td>0.601468</td>\n",
+              "      <td>0.481902</td>\n",
+              "      <td>0.606764</td>\n",
+              "      <td>0.585734</td>\n",
+              "      <td>0.607829</td>\n",
+              "      <td>0.211724</td>\n",
+              "      <td>0.258016</td>\n",
+              "      <td>0.269558</td>\n",
+              "      <td>0.055368</td>\n",
+              "      <td>-0.080918</td>\n",
+              "      <td>0.241065</td>\n",
+              "      <td>0.174539</td>\n",
+              "      <td>0.261489</td>\n",
+              "      <td>-0.021343</td>\n",
+              "      <td>0.636038</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Alcohol use</th>\n",
+              "      <td>0.151742</td>\n",
+              "      <td>-0.227636</td>\n",
+              "      <td>0.747293</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.818644</td>\n",
+              "      <td>0.878786</td>\n",
+              "      <td>0.877210</td>\n",
+              "      <td>0.763576</td>\n",
+              "      <td>0.653352</td>\n",
+              "      <td>0.669312</td>\n",
+              "      <td>0.547035</td>\n",
+              "      <td>0.592576</td>\n",
+              "      <td>0.717242</td>\n",
+              "      <td>0.667612</td>\n",
+              "      <td>0.237245</td>\n",
+              "      <td>0.207851</td>\n",
+              "      <td>0.435785</td>\n",
+              "      <td>0.180817</td>\n",
+              "      <td>-0.114073</td>\n",
+              "      <td>0.414992</td>\n",
+              "      <td>0.180778</td>\n",
+              "      <td>0.211277</td>\n",
+              "      <td>0.122694</td>\n",
+              "      <td>0.718710</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Dust Allergy</th>\n",
+              "      <td>0.035202</td>\n",
+              "      <td>-0.204312</td>\n",
+              "      <td>0.637503</td>\n",
+              "      <td>0.818644</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.835860</td>\n",
+              "      <td>0.787904</td>\n",
+              "      <td>0.619556</td>\n",
+              "      <td>0.647197</td>\n",
+              "      <td>0.700676</td>\n",
+              "      <td>0.358691</td>\n",
+              "      <td>0.560002</td>\n",
+              "      <td>0.639983</td>\n",
+              "      <td>0.625291</td>\n",
+              "      <td>0.332472</td>\n",
+              "      <td>0.321756</td>\n",
+              "      <td>0.518682</td>\n",
+              "      <td>0.304850</td>\n",
+              "      <td>0.031141</td>\n",
+              "      <td>0.345714</td>\n",
+              "      <td>0.219389</td>\n",
+              "      <td>0.300195</td>\n",
+              "      <td>0.052844</td>\n",
+              "      <td>0.713839</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>OccuPational Hazards</th>\n",
+              "      <td>0.062177</td>\n",
+              "      <td>-0.192343</td>\n",
+              "      <td>0.608924</td>\n",
+              "      <td>0.878786</td>\n",
+              "      <td>0.835860</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.893049</td>\n",
+              "      <td>0.858284</td>\n",
+              "      <td>0.691509</td>\n",
+              "      <td>0.722191</td>\n",
+              "      <td>0.497693</td>\n",
+              "      <td>0.555311</td>\n",
+              "      <td>0.775619</td>\n",
+              "      <td>0.645947</td>\n",
+              "      <td>0.267844</td>\n",
+              "      <td>0.176226</td>\n",
+              "      <td>0.366482</td>\n",
+              "      <td>0.178925</td>\n",
+              "      <td>-0.002853</td>\n",
+              "      <td>0.366447</td>\n",
+              "      <td>0.077166</td>\n",
+              "      <td>0.159887</td>\n",
+              "      <td>0.022916</td>\n",
+              "      <td>0.673255</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Genetic Risk</th>\n",
+              "      <td>0.073151</td>\n",
+              "      <td>-0.222727</td>\n",
+              "      <td>0.705276</td>\n",
+              "      <td>0.877210</td>\n",
+              "      <td>0.787904</td>\n",
+              "      <td>0.893049</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.836231</td>\n",
+              "      <td>0.679905</td>\n",
+              "      <td>0.729826</td>\n",
+              "      <td>0.543259</td>\n",
+              "      <td>0.609071</td>\n",
+              "      <td>0.831751</td>\n",
+              "      <td>0.632236</td>\n",
+              "      <td>0.230530</td>\n",
+              "      <td>0.271743</td>\n",
+              "      <td>0.458200</td>\n",
+              "      <td>0.204973</td>\n",
+              "      <td>-0.062948</td>\n",
+              "      <td>0.357815</td>\n",
+              "      <td>0.087092</td>\n",
+              "      <td>0.194399</td>\n",
+              "      <td>-0.056831</td>\n",
+              "      <td>0.701303</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>chronic Lung Disease</th>\n",
+              "      <td>0.128952</td>\n",
+              "      <td>-0.205061</td>\n",
+              "      <td>0.626701</td>\n",
+              "      <td>0.763576</td>\n",
+              "      <td>0.619556</td>\n",
+              "      <td>0.858284</td>\n",
+              "      <td>0.836231</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.622632</td>\n",
+              "      <td>0.601754</td>\n",
+              "      <td>0.578585</td>\n",
+              "      <td>0.572698</td>\n",
+              "      <td>0.782646</td>\n",
+              "      <td>0.602987</td>\n",
+              "      <td>0.247697</td>\n",
+              "      <td>0.104080</td>\n",
+              "      <td>0.182426</td>\n",
+              "      <td>0.057214</td>\n",
+              "      <td>0.007279</td>\n",
+              "      <td>0.298023</td>\n",
+              "      <td>0.028759</td>\n",
+              "      <td>0.114161</td>\n",
+              "      <td>0.043375</td>\n",
+              "      <td>0.609971</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Balanced Diet</th>\n",
+              "      <td>0.004863</td>\n",
+              "      <td>-0.099741</td>\n",
+              "      <td>0.524873</td>\n",
+              "      <td>0.653352</td>\n",
+              "      <td>0.647197</td>\n",
+              "      <td>0.691509</td>\n",
+              "      <td>0.679905</td>\n",
+              "      <td>0.622632</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.706922</td>\n",
+              "      <td>0.645390</td>\n",
+              "      <td>0.725123</td>\n",
+              "      <td>0.798207</td>\n",
+              "      <td>0.745054</td>\n",
+              "      <td>0.400678</td>\n",
+              "      <td>-0.006544</td>\n",
+              "      <td>0.343623</td>\n",
+              "      <td>0.063930</td>\n",
+              "      <td>0.046807</td>\n",
+              "      <td>0.041967</td>\n",
+              "      <td>0.263931</td>\n",
+              "      <td>0.331995</td>\n",
+              "      <td>0.152677</td>\n",
+              "      <td>0.706273</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Obesity</th>\n",
+              "      <td>0.034337</td>\n",
+              "      <td>-0.123813</td>\n",
+              "      <td>0.601468</td>\n",
+              "      <td>0.669312</td>\n",
+              "      <td>0.700676</td>\n",
+              "      <td>0.722191</td>\n",
+              "      <td>0.729826</td>\n",
+              "      <td>0.601754</td>\n",
+              "      <td>0.706922</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.486795</td>\n",
+              "      <td>0.681889</td>\n",
+              "      <td>0.673150</td>\n",
+              "      <td>0.814805</td>\n",
+              "      <td>0.552788</td>\n",
+              "      <td>0.313495</td>\n",
+              "      <td>0.406203</td>\n",
+              "      <td>0.094287</td>\n",
+              "      <td>0.127213</td>\n",
+              "      <td>0.149093</td>\n",
+              "      <td>0.288368</td>\n",
+              "      <td>0.200618</td>\n",
+              "      <td>0.039422</td>\n",
+              "      <td>0.827435</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Smoking</th>\n",
+              "      <td>0.075333</td>\n",
+              "      <td>-0.206924</td>\n",
+              "      <td>0.481902</td>\n",
+              "      <td>0.547035</td>\n",
+              "      <td>0.358691</td>\n",
+              "      <td>0.497693</td>\n",
+              "      <td>0.543259</td>\n",
+              "      <td>0.578585</td>\n",
+              "      <td>0.645390</td>\n",
+              "      <td>0.486795</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.761622</td>\n",
+              "      <td>0.647926</td>\n",
+              "      <td>0.555289</td>\n",
+              "      <td>0.200029</td>\n",
+              "      <td>-0.212937</td>\n",
+              "      <td>-0.023259</td>\n",
+              "      <td>-0.047060</td>\n",
+              "      <td>0.236141</td>\n",
+              "      <td>-0.041147</td>\n",
+              "      <td>0.039585</td>\n",
+              "      <td>0.010101</td>\n",
+              "      <td>0.189055</td>\n",
+              "      <td>0.519530</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Passive Smoker</th>\n",
+              "      <td>0.004908</td>\n",
+              "      <td>-0.184826</td>\n",
+              "      <td>0.606764</td>\n",
+              "      <td>0.592576</td>\n",
+              "      <td>0.560002</td>\n",
+              "      <td>0.555311</td>\n",
+              "      <td>0.609071</td>\n",
+              "      <td>0.572698</td>\n",
+              "      <td>0.725123</td>\n",
+              "      <td>0.681889</td>\n",
+              "      <td>0.761622</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.696077</td>\n",
+              "      <td>0.636223</td>\n",
+              "      <td>0.377919</td>\n",
+              "      <td>0.058336</td>\n",
+              "      <td>0.062948</td>\n",
+              "      <td>0.200283</td>\n",
+              "      <td>0.348922</td>\n",
+              "      <td>-0.035536</td>\n",
+              "      <td>0.104553</td>\n",
+              "      <td>0.120761</td>\n",
+              "      <td>0.247943</td>\n",
+              "      <td>0.703594</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Chest Pain</th>\n",
+              "      <td>0.012864</td>\n",
+              "      <td>-0.218426</td>\n",
+              "      <td>0.585734</td>\n",
+              "      <td>0.717242</td>\n",
+              "      <td>0.639983</td>\n",
+              "      <td>0.775619</td>\n",
+              "      <td>0.831751</td>\n",
+              "      <td>0.782646</td>\n",
+              "      <td>0.798207</td>\n",
+              "      <td>0.673150</td>\n",
+              "      <td>0.647926</td>\n",
+              "      <td>0.696077</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.712158</td>\n",
+              "      <td>0.251135</td>\n",
+              "      <td>-0.001092</td>\n",
+              "      <td>0.237045</td>\n",
+              "      <td>0.107211</td>\n",
+              "      <td>0.071784</td>\n",
+              "      <td>0.081386</td>\n",
+              "      <td>0.042937</td>\n",
+              "      <td>0.142180</td>\n",
+              "      <td>0.140036</td>\n",
+              "      <td>0.645461</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Coughing of Blood</th>\n",
+              "      <td>0.053006</td>\n",
+              "      <td>-0.146505</td>\n",
+              "      <td>0.607829</td>\n",
+              "      <td>0.667612</td>\n",
+              "      <td>0.625291</td>\n",
+              "      <td>0.645947</td>\n",
+              "      <td>0.632236</td>\n",
+              "      <td>0.602987</td>\n",
+              "      <td>0.745054</td>\n",
+              "      <td>0.814805</td>\n",
+              "      <td>0.555289</td>\n",
+              "      <td>0.636223</td>\n",
+              "      <td>0.712158</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.481540</td>\n",
+              "      <td>0.105857</td>\n",
+              "      <td>0.318777</td>\n",
+              "      <td>-0.085698</td>\n",
+              "      <td>0.086289</td>\n",
+              "      <td>-0.066443</td>\n",
+              "      <td>0.244235</td>\n",
+              "      <td>0.147659</td>\n",
+              "      <td>0.087944</td>\n",
+              "      <td>0.782092</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Fatigue</th>\n",
+              "      <td>0.095059</td>\n",
+              "      <td>-0.116467</td>\n",
+              "      <td>0.211724</td>\n",
+              "      <td>0.237245</td>\n",
+              "      <td>0.332472</td>\n",
+              "      <td>0.267844</td>\n",
+              "      <td>0.230530</td>\n",
+              "      <td>0.247697</td>\n",
+              "      <td>0.400678</td>\n",
+              "      <td>0.552788</td>\n",
+              "      <td>0.200029</td>\n",
+              "      <td>0.377919</td>\n",
+              "      <td>0.251135</td>\n",
+              "      <td>0.481540</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.469517</td>\n",
+              "      <td>0.398625</td>\n",
+              "      <td>0.174477</td>\n",
+              "      <td>0.149562</td>\n",
+              "      <td>0.040694</td>\n",
+              "      <td>0.407915</td>\n",
+              "      <td>0.271167</td>\n",
+              "      <td>0.231748</td>\n",
+              "      <td>0.625114</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Weight Loss</th>\n",
+              "      <td>0.106946</td>\n",
+              "      <td>-0.057993</td>\n",
+              "      <td>0.258016</td>\n",
+              "      <td>0.207851</td>\n",
+              "      <td>0.321756</td>\n",
+              "      <td>0.176226</td>\n",
+              "      <td>0.271743</td>\n",
+              "      <td>0.104080</td>\n",
+              "      <td>-0.006544</td>\n",
+              "      <td>0.313495</td>\n",
+              "      <td>-0.212937</td>\n",
+              "      <td>0.058336</td>\n",
+              "      <td>-0.001092</td>\n",
+              "      <td>0.105857</td>\n",
+              "      <td>0.469517</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.574497</td>\n",
+              "      <td>0.331179</td>\n",
+              "      <td>0.053384</td>\n",
+              "      <td>0.376484</td>\n",
+              "      <td>0.160348</td>\n",
+              "      <td>0.188598</td>\n",
+              "      <td>-0.189106</td>\n",
+              "      <td>0.352738</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Shortness of Breath</th>\n",
+              "      <td>0.035329</td>\n",
+              "      <td>-0.045972</td>\n",
+              "      <td>0.269558</td>\n",
+              "      <td>0.435785</td>\n",
+              "      <td>0.518682</td>\n",
+              "      <td>0.366482</td>\n",
+              "      <td>0.458200</td>\n",
+              "      <td>0.182426</td>\n",
+              "      <td>0.343623</td>\n",
+              "      <td>0.406203</td>\n",
+              "      <td>-0.023259</td>\n",
+              "      <td>0.062948</td>\n",
+              "      <td>0.237045</td>\n",
+              "      <td>0.318777</td>\n",
+              "      <td>0.398625</td>\n",
+              "      <td>0.574497</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.207564</td>\n",
+              "      <td>-0.200477</td>\n",
+              "      <td>0.474275</td>\n",
+              "      <td>0.351489</td>\n",
+              "      <td>0.493331</td>\n",
+              "      <td>-0.159291</td>\n",
+              "      <td>0.497024</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Wheezing</th>\n",
+              "      <td>-0.095354</td>\n",
+              "      <td>-0.076304</td>\n",
+              "      <td>0.055368</td>\n",
+              "      <td>0.180817</td>\n",
+              "      <td>0.304850</td>\n",
+              "      <td>0.178925</td>\n",
+              "      <td>0.204973</td>\n",
+              "      <td>0.057214</td>\n",
+              "      <td>0.063930</td>\n",
+              "      <td>0.094287</td>\n",
+              "      <td>-0.047060</td>\n",
+              "      <td>0.200283</td>\n",
+              "      <td>0.107211</td>\n",
+              "      <td>-0.085698</td>\n",
+              "      <td>0.174477</td>\n",
+              "      <td>0.331179</td>\n",
+              "      <td>0.207564</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.393487</td>\n",
+              "      <td>0.338271</td>\n",
+              "      <td>0.098855</td>\n",
+              "      <td>0.054388</td>\n",
+              "      <td>0.116183</td>\n",
+              "      <td>0.242794</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Swallowing Difficulty</th>\n",
+              "      <td>-0.105833</td>\n",
+              "      <td>-0.058324</td>\n",
+              "      <td>-0.080918</td>\n",
+              "      <td>-0.114073</td>\n",
+              "      <td>0.031141</td>\n",
+              "      <td>-0.002853</td>\n",
+              "      <td>-0.062948</td>\n",
+              "      <td>0.007279</td>\n",
+              "      <td>0.046807</td>\n",
+              "      <td>0.127213</td>\n",
+              "      <td>0.236141</td>\n",
+              "      <td>0.348922</td>\n",
+              "      <td>0.071784</td>\n",
+              "      <td>0.086289</td>\n",
+              "      <td>0.149562</td>\n",
+              "      <td>0.053384</td>\n",
+              "      <td>-0.200477</td>\n",
+              "      <td>0.393487</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>-0.119741</td>\n",
+              "      <td>0.132363</td>\n",
+              "      <td>-0.055428</td>\n",
+              "      <td>0.210540</td>\n",
+              "      <td>0.249142</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Clubbing of Finger Nails</th>\n",
+              "      <td>0.039258</td>\n",
+              "      <td>-0.034219</td>\n",
+              "      <td>0.241065</td>\n",
+              "      <td>0.414992</td>\n",
+              "      <td>0.345714</td>\n",
+              "      <td>0.366447</td>\n",
+              "      <td>0.357815</td>\n",
+              "      <td>0.298023</td>\n",
+              "      <td>0.041967</td>\n",
+              "      <td>0.149093</td>\n",
+              "      <td>-0.041147</td>\n",
+              "      <td>-0.035536</td>\n",
+              "      <td>0.081386</td>\n",
+              "      <td>-0.066443</td>\n",
+              "      <td>0.040694</td>\n",
+              "      <td>0.376484</td>\n",
+              "      <td>0.474275</td>\n",
+              "      <td>0.338271</td>\n",
+              "      <td>-0.119741</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.242529</td>\n",
+              "      <td>0.307271</td>\n",
+              "      <td>-0.017537</td>\n",
+              "      <td>0.280063</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Frequent Cold</th>\n",
+              "      <td>-0.012706</td>\n",
+              "      <td>-0.000526</td>\n",
+              "      <td>0.174539</td>\n",
+              "      <td>0.180778</td>\n",
+              "      <td>0.219389</td>\n",
+              "      <td>0.077166</td>\n",
+              "      <td>0.087092</td>\n",
+              "      <td>0.028759</td>\n",
+              "      <td>0.263931</td>\n",
+              "      <td>0.288368</td>\n",
+              "      <td>0.039585</td>\n",
+              "      <td>0.104553</td>\n",
+              "      <td>0.042937</td>\n",
+              "      <td>0.244235</td>\n",
+              "      <td>0.407915</td>\n",
+              "      <td>0.160348</td>\n",
+              "      <td>0.351489</td>\n",
+              "      <td>0.098855</td>\n",
+              "      <td>0.132363</td>\n",
+              "      <td>0.242529</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.515918</td>\n",
+              "      <td>0.335844</td>\n",
+              "      <td>0.444017</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Dry Cough</th>\n",
+              "      <td>0.012128</td>\n",
+              "      <td>-0.123001</td>\n",
+              "      <td>0.261489</td>\n",
+              "      <td>0.211277</td>\n",
+              "      <td>0.300195</td>\n",
+              "      <td>0.159887</td>\n",
+              "      <td>0.194399</td>\n",
+              "      <td>0.114161</td>\n",
+              "      <td>0.331995</td>\n",
+              "      <td>0.200618</td>\n",
+              "      <td>0.010101</td>\n",
+              "      <td>0.120761</td>\n",
+              "      <td>0.142180</td>\n",
+              "      <td>0.147659</td>\n",
+              "      <td>0.271167</td>\n",
+              "      <td>0.188598</td>\n",
+              "      <td>0.493331</td>\n",
+              "      <td>0.054388</td>\n",
+              "      <td>-0.055428</td>\n",
+              "      <td>0.307271</td>\n",
+              "      <td>0.515918</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.176146</td>\n",
+              "      <td>0.373968</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Snoring</th>\n",
+              "      <td>-0.004700</td>\n",
+              "      <td>-0.181618</td>\n",
+              "      <td>-0.021343</td>\n",
+              "      <td>0.122694</td>\n",
+              "      <td>0.052844</td>\n",
+              "      <td>0.022916</td>\n",
+              "      <td>-0.056831</td>\n",
+              "      <td>0.043375</td>\n",
+              "      <td>0.152677</td>\n",
+              "      <td>0.039422</td>\n",
+              "      <td>0.189055</td>\n",
+              "      <td>0.247943</td>\n",
+              "      <td>0.140036</td>\n",
+              "      <td>0.087944</td>\n",
+              "      <td>0.231748</td>\n",
+              "      <td>-0.189106</td>\n",
+              "      <td>-0.159291</td>\n",
+              "      <td>0.116183</td>\n",
+              "      <td>0.210540</td>\n",
+              "      <td>-0.017537</td>\n",
+              "      <td>0.335844</td>\n",
+              "      <td>0.176146</td>\n",
+              "      <td>1.000000</td>\n",
+              "      <td>0.289366</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Level</th>\n",
+              "      <td>0.060048</td>\n",
+              "      <td>-0.164985</td>\n",
+              "      <td>0.636038</td>\n",
+              "      <td>0.718710</td>\n",
+              "      <td>0.713839</td>\n",
+              "      <td>0.673255</td>\n",
+              "      <td>0.701303</td>\n",
+              "      <td>0.609971</td>\n",
+              "      <td>0.706273</td>\n",
+              "      <td>0.827435</td>\n",
+              "      <td>0.519530</td>\n",
+              "      <td>0.703594</td>\n",
+              "      <td>0.645461</td>\n",
+              "      <td>0.782092</td>\n",
+              "      <td>0.625114</td>\n",
+              "      <td>0.352738</td>\n",
+              "      <td>0.497024</td>\n",
+              "      <td>0.242794</td>\n",
+              "      <td>0.249142</td>\n",
+              "      <td>0.280063</td>\n",
+              "      <td>0.444017</td>\n",
+              "      <td>0.373968</td>\n",
+              "      <td>0.289366</td>\n",
+              "      <td>1.000000</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                               Age    Gender  ...   Snoring     Level\n",
+              "Age                       1.000000 -0.202086  ... -0.004700  0.060048\n",
+              "Gender                   -0.202086  1.000000  ... -0.181618 -0.164985\n",
+              "Air Pollution             0.099494 -0.246912  ... -0.021343  0.636038\n",
+              "Alcohol use               0.151742 -0.227636  ...  0.122694  0.718710\n",
+              "Dust Allergy              0.035202 -0.204312  ...  0.052844  0.713839\n",
+              "OccuPational Hazards      0.062177 -0.192343  ...  0.022916  0.673255\n",
+              "Genetic Risk              0.073151 -0.222727  ... -0.056831  0.701303\n",
+              "chronic Lung Disease      0.128952 -0.205061  ...  0.043375  0.609971\n",
+              "Balanced Diet             0.004863 -0.099741  ...  0.152677  0.706273\n",
+              "Obesity                   0.034337 -0.123813  ...  0.039422  0.827435\n",
+              "Smoking                   0.075333 -0.206924  ...  0.189055  0.519530\n",
+              "Passive Smoker            0.004908 -0.184826  ...  0.247943  0.703594\n",
+              "Chest Pain                0.012864 -0.218426  ...  0.140036  0.645461\n",
+              "Coughing of Blood         0.053006 -0.146505  ...  0.087944  0.782092\n",
+              "Fatigue                   0.095059 -0.116467  ...  0.231748  0.625114\n",
+              "Weight Loss               0.106946 -0.057993  ... -0.189106  0.352738\n",
+              "Shortness of Breath       0.035329 -0.045972  ... -0.159291  0.497024\n",
+              "Wheezing                 -0.095354 -0.076304  ...  0.116183  0.242794\n",
+              "Swallowing Difficulty    -0.105833 -0.058324  ...  0.210540  0.249142\n",
+              "Clubbing of Finger Nails  0.039258 -0.034219  ... -0.017537  0.280063\n",
+              "Frequent Cold            -0.012706 -0.000526  ...  0.335844  0.444017\n",
+              "Dry Cough                 0.012128 -0.123001  ...  0.176146  0.373968\n",
+              "Snoring                  -0.004700 -0.181618  ...  1.000000  0.289366\n",
+              "Level                     0.060048 -0.164985  ...  0.289366  1.000000\n",
+              "\n",
+              "[24 rows x 24 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 12
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 596
+        },
+        "id": "0489eiBaX6-W",
+        "outputId": "20f594b9-b24b-47da-d714-518ab4a490a8"
+      },
+      "source": [
+        "# As we can see we cannot understand from the data only so we will prepare a heatmap\n",
+        "plt.figure(figsize=(20, 8))\n",
+        "sns.heatmap(data.corr(), cmap=\"RdYlBu\", annot=True)\n",
+        "plt.show()"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 1440x576 with 2 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ZIB16p4eYyZB"
+      },
+      "source": [
+        "##Feature Selection and Extraction"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "t0OVOzicX97T"
+      },
+      "source": [
+        "array = data.values\n",
+        "X = array[:, 0:23]\n",
+        "Y = array[:, 23]"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CWBH8U-opqi5"
+      },
+      "source": [
+        "Feature extraction"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "OrT2iY-Y2PCf"
+      },
+      "source": [
+        "from sklearn.feature_selection import SelectKBest\n",
+        "from sklearn.feature_selection import chi2"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "XlodOS1Bpb_e"
+      },
+      "source": [
+        "# feature extraction\n",
+        "\n",
+        "test = SelectKBest(score_func=chi2, k=10)\n",
+        "fitt = test.fit(X, Y)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "eHSXrf0AqAVX",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "ad93a104-4d6c-419b-c0f8-a048ddc468d3"
+      },
+      "source": [
+        "# summarize scores\n",
+        "\n",
+        "print(fitt.scores_)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "[ 44.1872019    4.66816478 518.63153298 781.90984132 401.04088307\n",
+            " 415.68565443 488.6497259  302.39615669 588.9337429  712.08756223\n",
+            " 671.00625311 752.95979136 524.48952111 818.66888369 518.90044626\n",
+            " 206.66656281 330.88070877 201.4261893  113.07424926 257.90767922\n",
+            " 192.71327574 152.02954698  91.7481552 ]\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Grpj7t7JqL8u"
+      },
+      "source": [
+        "features = fitt.transform(X)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "zLr3wM2jqSLT",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "411fbcb1-cdf2-469f-a4f2-e88c2918f6d4"
+      },
+      "source": [
+        "# summarize selected features\n",
+        "print(\"Some rows of the selected features:\\n\")\n",
+        "print(features[0:5, :])"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Some rows of the selected features:\n",
+            "\n",
+            "[[2 4 3 2 4 3 2 2 4 3]\n",
+            " [3 1 4 2 2 2 4 2 3 1]\n",
+            " [4 5 5 6 7 2 3 4 8 8]\n",
+            " [7 7 6 7 7 7 7 7 8 4]\n",
+            " [6 8 7 7 7 8 7 7 9 3]]\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CkkkSui5pY0h"
+      },
+      "source": [
+        "#Scaling"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "-4cCRHnAs3n-"
+      },
+      "source": [
+        "Using Train Test Split"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "HZdtAub-uhyL"
+      },
+      "source": [
+        "from sklearn.model_selection import train_test_split"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Av9NrB3XpaNm"
+      },
+      "source": [
+        "x_train, x_test, y_train, y_test = train_test_split(features, Y, test_size=.33, random_state=0)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "imshUcNTurG0"
+      },
+      "source": [
+        "from sklearn.preprocessing import StandardScaler"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "GTaMxndVs7BU"
+      },
+      "source": [
+        "# Using StandardScaler to scale our data.\n",
+        "SC = StandardScaler()  "
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "YI8o_OJwtFfO"
+      },
+      "source": [
+        "x_train = SC.fit_transform(x_train)\n",
+        "x_test = SC.transform(x_test)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "EY3zlAq_qWiF"
+      },
+      "source": [
+        "#Model Training"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "5pVdshkGqZ8k"
+      },
+      "source": [
+        "Model 1: Logistic Regression"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "ZqiqRHSxqYIA"
+      },
+      "source": [
+        "from sklearn.linear_model import LogisticRegression"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "6ZignPY0ri6A"
+      },
+      "source": [
+        "model = LogisticRegression()"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "MBjn-7JErn8O"
+      },
+      "source": [
+        "model.fit(x_train, y_train)\n",
+        "prediction = model.predict(x_test)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "TjMQUTVbrqQb"
+      },
+      "source": [
+        "from sklearn.metrics import accuracy_score"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "PvazebHRr_02",
+        "outputId": "54ddc9f2-18e4-43e4-e9dc-94eddbc8f040"
+      },
+      "source": [
+        "acc = accuracy_score(prediction, y_test)\n",
+        "print(\"\\nAccuracy of Logistic Regression:\", round(acc * 100, 2), \"%\")"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "\n",
+            "Accuracy of Logistic Regression: 91.21 %\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "vAblOFPWsT4f"
+      },
+      "source": [
+        "Model 2: SVM (Support Vector Machine)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "cwJ5oPUSsWC9"
+      },
+      "source": [
+        "from sklearn.svm import SVC"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "xtnJXE5ZsfBU"
+      },
+      "source": [
+        "model2 = SVC(kernel='linear')"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "GzuaiUR3slNZ"
+      },
+      "source": [
+        "model2.fit(x_train, y_train)\n",
+        "prediction2 = model2.predict(x_test)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "2Ir3HZ6cspVN",
+        "outputId": "e34eb72e-c044-4999-ff52-aca63866eb25"
+      },
+      "source": [
+        "acc2 = accuracy_score(prediction2, y_test)\n",
+        "print(\"\\nAccuracy of SVM:\", round(acc2 * 100, 2), \"%\")"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "\n",
+            "Accuracy of SVM: 92.12 %\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "pzmr-FiBwDFs"
+      },
+      "source": [
+        ""
+      ],
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file