sklearn-mushroomDataset.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[{"file_id":"1RHW0gnjwuLLHgWsfm7fUhs5nvgIZdKBO","timestamp":1693587240065}],"authorship_tag":"ABX9TyPktcpyXqznrUIBzomJc9NK"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":null,"metadata":{"id":"RDOcZROPd3PZ"},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","import matplotlib as plt\n","\n","# AI related imports\n","from sklearn.preprocessing import LabelEncoder\n","from sklearn.model_selection import train_test_split\n","from sklearn.linear_model import LogisticRegression as LR\n","from sklearn.ensemble import RandomForestClassifier as RFC\n","from sklearn.metrics import confusion_matrix, accuracy_score"]},{"cell_type":"code","source":["columnNames = ['edible?', 'cap-shape', 'cap-surface', 'cap-color', 'bruises', 'odor', 'gill-attachment', 'gill-spacing',\n","               'gill-size', 'gill-color', 'stalk-shape', 'stalk-root', 'stalk-surface-above-ring', 'stalk-surface-below-ring',\n","               'stalk-color-above-ring', 'stalk-color-below-ring', 'veil-type', 'veil-color', 'ring-number', 'ring-type',\n","               'spore-print-color', 'population', 'habitat']\n","df = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/agaricus-lepiota.data', names=columnNames, dtype=str)\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":297},"id":"_Hsft7mMeNQc","executionInfo":{"status":"ok","timestamp":1680685622955,"user_tz":-330,"elapsed":1314,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"ffc9870f-b4fa-4e43-9b66-4f77516853fa"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["  edible? cap-shape cap-surface cap-color bruises odor gill-attachment  \\\n","0       p         x           s         n       t    p               f   \n","1       e         x           s         y       t    a               f   \n","2       e         b           s         w       t    l               f   \n","3       p         x           y         w       t    p               f   \n","4       e         x           s         g       f    n               f   \n","\n","  gill-spacing gill-size gill-color  ... stalk-surface-below-ring  \\\n","0            c         n          k  ...                        s   \n","1            c         b          k  ...                        s   \n","2            c         b          n  ...                        s   \n","3            c         n          n  ...                        s   \n","4            w         b          k  ...                        s   \n","\n","  stalk-color-above-ring stalk-color-below-ring veil-type veil-color  \\\n","0                      w                      w         p          w   \n","1                      w                      w         p          w   \n","2                      w                      w         p          w   \n","3                      w                      w         p          w   \n","4                      w                      w         p          w   \n","\n","  ring-number ring-type spore-print-color population habitat  \n","0           o         p                 k          s       u  \n","1           o         p                 n          n       g  \n","2           o         p                 n          n       m  \n","3           o         p                 k          s       u  \n","4           o         e                 n          a       g  \n","\n","[5 rows x 23 columns]"],"text/html":["\n","  <div id=\"df-19637dea-f466-409f-a7cb-7bf91f4f0e3a\">\n","    <div class=\"colab-df-container\">\n","      <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>edible?</th>\n","      <th>cap-shape</th>\n","      <th>cap-surface</th>\n","      <th>cap-color</th>\n","      <th>bruises</th>\n","      <th>odor</th>\n","      <th>gill-attachment</th>\n","      <th>gill-spacing</th>\n","      <th>gill-size</th>\n","      <th>gill-color</th>\n","      <th>...</th>\n","      <th>stalk-surface-below-ring</th>\n","      <th>stalk-color-above-ring</th>\n","      <th>stalk-color-below-ring</th>\n","      <th>veil-type</th>\n","      <th>veil-color</th>\n","      <th>ring-number</th>\n","      <th>ring-type</th>\n","      <th>spore-print-color</th>\n","      <th>population</th>\n","      <th>habitat</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>p</td>\n","      <td>x</td>\n","      <td>s</td>\n","      <td>n</td>\n","      <td>t</td>\n","      <td>p</td>\n","      <td>f</td>\n","      <td>c</td>\n","      <td>n</td>\n","      <td>k</td>\n","      <td>...</td>\n","      <td>s</td>\n","      <td>w</td>\n","      <td>w</td>\n","      <td>p</td>\n","      <td>w</td>\n","      <td>o</td>\n","      <td>p</td>\n","      <td>k</td>\n","      <td>s</td>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>e</td>\n","      <td>x</td>\n","      <td>s</td>\n","      <td>y</td>\n","      <td>t</td>\n","      <td>a</td>\n","      <td>f</td>\n","      <td>c</td>\n","      <td>b</td>\n","      <td>k</td>\n","      <td>...</td>\n","      <td>s</td>\n","      <td>w</td>\n","      <td>w</td>\n","      <td>p</td>\n","      <td>w</td>\n","      <td>o</td>\n","      <td>p</td>\n","      <td>n</td>\n","      <td>n</td>\n","      <td>g</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>e</td>\n","      <td>b</td>\n","      <td>s</td>\n","      <td>w</td>\n","      <td>t</td>\n","      <td>l</td>\n","      <td>f</td>\n","      <td>c</td>\n","      <td>b</td>\n","      <td>n</td>\n","      <td>...</td>\n","      <td>s</td>\n","      <td>w</td>\n","      <td>w</td>\n","      <td>p</td>\n","      <td>w</td>\n","      <td>o</td>\n","      <td>p</td>\n","      <td>n</td>\n","      <td>n</td>\n","      <td>m</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>p</td>\n","      <td>x</td>\n","      <td>y</td>\n","      <td>w</td>\n","      <td>t</td>\n","      <td>p</td>\n","      <td>f</td>\n","      <td>c</td>\n","      <td>n</td>\n","      <td>n</td>\n","      <td>...</td>\n","      <td>s</td>\n","      <td>w</td>\n","      <td>w</td>\n","      <td>p</td>\n","      <td>w</td>\n","      <td>o</td>\n","      <td>p</td>\n","      <td>k</td>\n","      <td>s</td>\n","      <td>u</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>e</td>\n","      <td>x</td>\n","      <td>s</td>\n","      <td>g</td>\n","      <td>f</td>\n","      <td>n</td>\n","      <td>f</td>\n","      <td>w</td>\n","      <td>b</td>\n","      <td>k</td>\n","      <td>...</td>\n","      <td>s</td>\n","      <td>w</td>\n","      <td>w</td>\n","      <td>p</td>\n","      <td>w</td>\n","      <td>o</td>\n","      <td>e</td>\n","      <td>n</td>\n","      <td>a</td>\n","      <td>g</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 23 columns</p>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-19637dea-f466-409f-a7cb-7bf91f4f0e3a')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-19637dea-f466-409f-a7cb-7bf91f4f0e3a button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 'block' : 'none';\n","\n","        async function convertToInteractive(key) {\n","          const element = document.querySelector('#df-19637dea-f466-409f-a7cb-7bf91f4f0e3a');\n","          const dataTable =\n","            await google.colab.kernel.invokeFunction('convertToInteractive',\n","                                                     [key], {});\n","          if (!dataTable) return;\n","\n","          const docLinkHtml = 'Like what you see? Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n","  "]},"metadata":{},"execution_count":84}]},{"cell_type":"code","source":["print(f\"Number of Poisonous Mushrooms: {df['edible?'].value_counts()[1]}\\nNumber of Edible Mushrooms: {df['edible?'].value_counts()[0]}\")\n","print(f\"Shape of df = {df.shape}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"P1cNxi7GeTDr","executionInfo":{"status":"ok","timestamp":1680685622955,"user_tz":-330,"elapsed":14,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"c462c69f-527d-4341-a3e5-6106a19c5ad4"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Number of Poisonous Mushrooms: 3916\n","Number of Edible Mushrooms: 4208\n","Shape of df = (8124, 23)\n"]}]},{"cell_type":"code","source":["# finding missing values (labelled as '?')\n","df.isin(['?']).sum()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"gHBGqj99h4gl","executionInfo":{"status":"ok","timestamp":1680685622955,"user_tz":-330,"elapsed":13,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"ef06e67f-bb86-4731-cb62-a1f64043ae97"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["edible?                        0\n","cap-shape                      0\n","cap-surface                    0\n","cap-color                      0\n","bruises                        0\n","odor                           0\n","gill-attachment                0\n","gill-spacing                   0\n","gill-size                      0\n","gill-color                     0\n","stalk-shape                    0\n","stalk-root                  2480\n","stalk-surface-above-ring       0\n","stalk-surface-below-ring       0\n","stalk-color-above-ring         0\n","stalk-color-below-ring         0\n","veil-type                      0\n","veil-color                     0\n","ring-number                    0\n","ring-type                      0\n","spore-print-color              0\n","population                     0\n","habitat                        0\n","dtype: int64"]},"metadata":{},"execution_count":86}]},{"cell_type":"code","source":["# using Modal impute\n","df.replace({'?': df['stalk-root'].mode()[0]}, inplace=True)\n","# check if data is clean\n","df.isin(['?']).sum().sum() == 0"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"GT4kvjQfkL93","executionInfo":{"status":"ok","timestamp":1680685622955,"user_tz":-330,"elapsed":12,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"6e47490a-6b52-4ed7-fbc7-007ae20bd41b"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["True"]},"metadata":{},"execution_count":87}]},{"cell_type":"code","source":["# Remove unwanted features\n","df.var()\n","\"\"\"\n","edible?                      0.249708\n","cap-shape                    2.573872\n","cap-surface                  1.512586\n","cap-color                    6.481204\n","bruises                      0.242900\n","odor                         4.425676\n","gill-attachment              0.025184\n","gill-spacing                 0.135432\n","gill-size                    0.213624\n","gill-color                  12.534142\n","stalk-shape                  0.245513\n","stalk-root                   3.040309\n","stalk-surface-above-ring     0.386212\n","stalk-surface-below-ring     0.456941\n","stalk-color-above-ring       3.616643\n","stalk-color-below-ring       3.637761\n","veil-type                    0.000000\n","veil-color                   0.058888\n","ring-number                  0.073476\n","ring-type                    3.246022\n","spore-print-color            5.677084\n","population                   1.567709\n","habitat                      2.958316\n","\"\"\"\n","# from this array, veil-type, gill-attachment, veil-color, ring-number can be removed\n","df.drop(['veil-type', 'gill-attachment', 'veil-color', 'ring-number'], axis='columns', inplace=True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"v3RxbgFtpcqv","executionInfo":{"status":"ok","timestamp":1680685622956,"user_tz":-330,"elapsed":12,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"1a3fa589-919e-46e9-df16-36df25b5fc1b"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["<ipython-input-88-e6ca1c0ea931>:2: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError.  Select only valid columns before calling the reduction.\n","  df.var()\n"]}]},{"cell_type":"code","source":["# Label encoding the df\n","for column in df.columns:\n","    df[column] = LabelEncoder().fit_transform(df[column])\n","df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":268},"id":"dupme_Iloqoh","executionInfo":{"status":"ok","timestamp":1680685622956,"user_tz":-330,"elapsed":11,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"ab55ea50-e411-4a12-dc78-10ea50f59578"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["   edible?  cap-shape  cap-surface  cap-color  bruises  odor  gill-spacing  \\\n","0        1          5            2          4        1     6             0   \n","1        0          5            2          9        1     0             0   \n","2        0          0            2          8        1     3             0   \n","3        1          5            3          8        1     6             0   \n","4        0          5            2          3        0     5             1   \n","\n","   gill-size  gill-color  stalk-shape  stalk-root  stalk-surface-above-ring  \\\n","0          1           4            0           2                         2   \n","1          0           4            0           1                         2   \n","2          0           5            0           1                         2   \n","3          1           5            0           2                         2   \n","4          0           4            1           2                         2   \n","\n","   stalk-surface-below-ring  stalk-color-above-ring  stalk-color-below-ring  \\\n","0                         2                       7                       7   \n","1                         2                       7                       7   \n","2                         2                       7                       7   \n","3                         2                       7                       7   \n","4                         2                       7                       7   \n","\n","   ring-type  spore-print-color  population  habitat  \n","0          4                  2           3        5  \n","1          4                  3           2        1  \n","2          4                  3           2        3  \n","3          4                  2           3        5  \n","4          0                  3           0        1  "],"text/html":["\n","  <div id=\"df-36369cd0-b9a1-4732-8aac-52043bdb2809\">\n","    <div class=\"colab-df-container\">\n","      <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>edible?</th>\n","      <th>cap-shape</th>\n","      <th>cap-surface</th>\n","      <th>cap-color</th>\n","      <th>bruises</th>\n","      <th>odor</th>\n","      <th>gill-spacing</th>\n","      <th>gill-size</th>\n","      <th>gill-color</th>\n","      <th>stalk-shape</th>\n","      <th>stalk-root</th>\n","      <th>stalk-surface-above-ring</th>\n","      <th>stalk-surface-below-ring</th>\n","      <th>stalk-color-above-ring</th>\n","      <th>stalk-color-below-ring</th>\n","      <th>ring-type</th>\n","      <th>spore-print-color</th>\n","      <th>population</th>\n","      <th>habitat</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>5</td>\n","      <td>2</td>\n","      <td>4</td>\n","      <td>1</td>\n","      <td>6</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>4</td>\n","      <td>0</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>7</td>\n","      <td>7</td>\n","      <td>4</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>5</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0</td>\n","      <td>5</td>\n","      <td>2</td>\n","      <td>9</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>4</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>7</td>\n","      <td>7</td>\n","      <td>4</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>2</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>3</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>5</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>7</td>\n","      <td>7</td>\n","      <td>4</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>3</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>5</td>\n","      <td>3</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>6</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>5</td>\n","      <td>0</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>7</td>\n","      <td>7</td>\n","      <td>4</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>5</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0</td>\n","      <td>5</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>0</td>\n","      <td>5</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>4</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>7</td>\n","      <td>7</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-36369cd0-b9a1-4732-8aac-52043bdb2809')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-36369cd0-b9a1-4732-8aac-52043bdb2809 button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 'block' : 'none';\n","\n","        async function convertToInteractive(key) {\n","          const element = document.querySelector('#df-36369cd0-b9a1-4732-8aac-52043bdb2809');\n","          const dataTable =\n","            await google.colab.kernel.invokeFunction('convertToInteractive',\n","                                                     [key], {});\n","          if (!dataTable) return;\n","\n","          const docLinkHtml = 'Like what you see? Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n","  "]},"metadata":{},"execution_count":89}]},{"cell_type":"code","source":["# defining X and y\n","X = df.iloc[:, 1:].to_numpy()\n","y = df.iloc[:, 0].to_numpy()"],"metadata":{"id":"LBA-AjXYmoSO"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# spliting into train and test sets\n","X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, shuffle=True)\n","len(X_train) == len(y_train)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jOBLfJELmdhC","executionInfo":{"status":"ok","timestamp":1680685622956,"user_tz":-330,"elapsed":11,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"915d6a79-6edb-4e75-d3f2-d4c8c628c8c1"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["True"]},"metadata":{},"execution_count":91}]},{"cell_type":"code","source":["# making the model\n","RFmodel = RFC(n_estimators=2, random_state=42)\n","RFmodel.fit(X_train, y_train)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":75},"id":"RRXaS8xKnXsS","executionInfo":{"status":"ok","timestamp":1680685622957,"user_tz":-330,"elapsed":11,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"284d0a44-2579-4f80-8303-f7b419a30cf6"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["RandomForestClassifier(n_estimators=2, random_state=42)"],"text/html":["<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestClassifier(n_estimators=2, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestClassifier</label><div class=\"sk-toggleable__content\"><pre>RandomForestClassifier(n_estimators=2, random_state=42)</pre></div></div></div></div></div>"]},"metadata":{},"execution_count":92}]},{"cell_type":"code","source":["y_pred = RFmodel.predict(X_test)\n","print(f\"Random Forest Classifier statistics:\\n----------------\\nAccuracy: {accuracy_score(y_test, y_pred)*100:.4f}%\\n\\nConfusion Matrix:\\n{confusion_matrix(y_test, y_pred)}\\n----------------\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"bKmfPWDfpY7P","executionInfo":{"status":"ok","timestamp":1680686036668,"user_tz":-330,"elapsed":714,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"c105204e-bbeb-4329-81a3-166c8165ffaf"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Random Forest Classifier statistics:\n","----------------\n","Accuracy: 99.9180%\n","\n","Confusion Matrix:\n","[[1272    0]\n"," [   2 1164]]\n","----------------\n"]}]},{"cell_type":"code","source":["LRmodel = LR(max_iter=500)\n","LRmodel.fit(X_train, y_train)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":75},"id":"14ooIiSUr1W0","executionInfo":{"status":"ok","timestamp":1680685917464,"user_tz":-330,"elapsed":11,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"9f5155ef-1f27-473c-a12a-d1ca8c915e1f"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["LogisticRegression(max_iter=500)"],"text/html":["<style>#sk-container-id-4 {color: black;background-color: white;}#sk-container-id-4 pre{padding: 0;}#sk-container-id-4 div.sk-toggleable {background-color: white;}#sk-container-id-4 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-4 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-4 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-4 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-4 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-4 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-4 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-4 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-4 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-4 div.sk-item {position: relative;z-index: 1;}#sk-container-id-4 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-4 div.sk-item::before, #sk-container-id-4 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-4 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-4 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-4 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-4 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-4 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-4 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-4 div.sk-label-container {text-align: center;}#sk-container-id-4 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-4 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(max_iter=500)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" checked><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LogisticRegression</label><div class=\"sk-toggleable__content\"><pre>LogisticRegression(max_iter=500)</pre></div></div></div></div></div>"]},"metadata":{},"execution_count":104}]},{"cell_type":"code","source":["LRy_pred = LRmodel.predict(X_test)\n","print(f\"Logistic Regression statistics:\\n----------------\\nAccuracy: {accuracy_score(y_test, LRy_pred)*100:.4f}%\\n\\nConfusion Matrix:\\n{confusion_matrix(y_test, LRy_pred)}\\n----------------\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"fOnyxS9xsBGT","executionInfo":{"status":"ok","timestamp":1680686051179,"user_tz":-330,"elapsed":723,"user":{"displayName":"Anand Chauhan","userId":"12250269168455404130"}},"outputId":"7fe3d3c8-a5ab-4bcf-80c6-7a2b13dc7c47"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Logistic Regression statistics:\n","----------------\n","Accuracy: 94.7498%\n","\n","Confusion Matrix:\n","[[1211   61]\n"," [  67 1099]]\n","----------------\n"]}]}]}