AutoML_PyCaret_Regression_Classification_Sample.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "## PyCaret AutoML Sample Code"
      ],
      "metadata": {
        "id": "A_f8LpBfVNGC"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sb86S4hxtJDt",
        "outputId": "f95114cb-8bfd-4932-cba0-842923438ba6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Requirement already satisfied: webencodings in /usr/local/lib/python3.10/dist-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.5->pycaret) (0.5.1)\n",
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            "Building wheels for collected packages: pyod\n",
            "  Building wheel for pyod (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pyod: filename=pyod-1.0.9-py3-none-any.whl size=184097 sha256=5c885856efb5731c80232e398392a0026a7eae23af2dd91d065db13c0b973cee\n",
            "  Stored in directory: /root/.cache/pip/wheels/83/55/6b/552e083cf5509c0afe808b76cf434f1be284d01a112623bd37\n",
            "Successfully built pyod\n",
            "Installing collected packages: trace-updater, kaleido, dash-table, dash-html-components, dash-core-components, xxhash, wurlitzer, Werkzeug, tsdownsample, schemdraw, retrying, orjson, jedi, importlib-metadata, deprecation, deprecated, ansi2html, sktime, scikit-plot, pyod, dash, pmdarima, jupyter-dash, category-encoders, tbats, plotly-resampler, pycaret\n",
            "  Attempting uninstall: Werkzeug\n",
            "    Found existing installation: Werkzeug 2.3.0\n",
            "    Uninstalling Werkzeug-2.3.0:\n",
            "      Successfully uninstalled Werkzeug-2.3.0\n",
            "Successfully installed Werkzeug-2.2.3 ansi2html-1.9.0rc1 category-encoders-2.6.1 dash-2.10.2 dash-core-components-2.0.0 dash-html-components-2.0.0 dash-table-5.0.0 deprecated-1.2.14 deprecation-2.1.0 importlib-metadata-6.6.0 jedi-0.18.2 jupyter-dash-0.4.2 kaleido-0.2.1 orjson-3.9.1 plotly-resampler-0.9.0rc5 pmdarima-2.0.3 pycaret-3.0.2 pyod-1.0.9 retrying-1.3.4 schemdraw-0.15 scikit-plot-0.3.7 sktime-0.17.0 tbats-1.1.3 trace-updater-0.0.9.1 tsdownsample-0.1.2 wurlitzer-3.0.3 xxhash-3.2.0\n"
          ]
        }
      ],
      "source": [
        "!pip install --pre pycaret"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "B2-GUmmzNpoX"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Regression"
      ],
      "metadata": {
        "id": "OGsOgSJbDZL_"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "TvCb1PJgtnct",
        "outputId": "7efb6ac8-1eb7-4794-ebb7-fc40874e6136"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      manufacturer_name  model_name transmission   color  odometer_value  \\\n",
              "0                Subaru     Outback    automatic  silver          190000   \n",
              "1                Subaru     Outback    automatic    blue          290000   \n",
              "2                Subaru    Forester    automatic     red          402000   \n",
              "3                Subaru     Impreza   mechanical    blue           10000   \n",
              "4                Subaru      Legacy    automatic   black          280000   \n",
              "...                 ...         ...          ...     ...             ...   \n",
              "38526          Chrysler         300    automatic  silver          290000   \n",
              "38527          Chrysler  PT Cruiser   mechanical    blue          321000   \n",
              "38528          Chrysler         300    automatic    blue          777957   \n",
              "38529          Chrysler  PT Cruiser   mechanical   black           20000   \n",
              "38530          Chrysler     Voyager    automatic  silver          297729   \n",
              "\n",
              "       year_produced engine_fuel  engine_has_gas engine_type  engine_capacity  \\\n",
              "0               2012    gasoline           False    gasoline              2.5   \n",
              "1               2004    gasoline           False    gasoline              3.0   \n",
              "2               2003    gasoline           False    gasoline              2.5   \n",
              "3               2001    gasoline           False    gasoline              3.0   \n",
              "4               2003    gasoline           False    gasoline              2.5   \n",
              "...              ...         ...             ...         ...              ...   \n",
              "38526           2002    gasoline           False    gasoline              3.5   \n",
              "38527           2006      diesel           False      diesel              2.2   \n",
              "38528           2002    gasoline           False    gasoline              3.5   \n",
              "38529           2003    gasoline           False    gasoline              2.0   \n",
              "38530           2002    gasoline           False    gasoline              2.4   \n",
              "\n",
              "       body_type  has_warranty  state drivetrain  price_usd  is_exchangeable  \\\n",
              "0      universal         False  owned        all  15260.000            False   \n",
              "1      universal         False  owned        all   7000.000             True   \n",
              "2            suv         False  owned        all   3920.000             True   \n",
              "3          sedan         False  owned        all  13998.600             True   \n",
              "4      universal         False  owned        all   2987.754             True   \n",
              "...          ...           ...    ...        ...        ...              ...   \n",
              "38526      sedan         False  owned      front   3850.000             True   \n",
              "38527  hatchback         False  owned      front   6720.000             True   \n",
              "38528      sedan         False  owned      front   6020.000            False   \n",
              "38529    minivan         False  owned      front   5600.000             True   \n",
              "38530    minivan         False  owned      front   4480.000             True   \n",
              "\n",
              "       number_of_photos  up_counter  duration_listed  \n",
              "0                   4.5         6.5              8.0  \n",
              "1                   6.0        27.0             41.5  \n",
              "2                   2.0        36.0             75.5  \n",
              "3                   4.5        21.0             43.0  \n",
              "4                   7.0         3.5              3.5  \n",
              "...                 ...         ...              ...  \n",
              "38526               2.5        42.5            150.5  \n",
              "38527               2.0        10.0            158.5  \n",
              "38528               1.5        31.5            184.5  \n",
              "38529               3.5        78.0            245.0  \n",
              "38530               2.0        36.5            316.0  \n",
              "\n",
              "[38531 rows x 19 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-42d61d17-ba58-441a-98de-f9fe8675e3fd\">\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>manufacturer_name</th>\n",
              "      <th>model_name</th>\n",
              "      <th>transmission</th>\n",
              "      <th>color</th>\n",
              "      <th>odometer_value</th>\n",
              "      <th>year_produced</th>\n",
              "      <th>engine_fuel</th>\n",
              "      <th>engine_has_gas</th>\n",
              "      <th>engine_type</th>\n",
              "      <th>engine_capacity</th>\n",
              "      <th>body_type</th>\n",
              "      <th>has_warranty</th>\n",
              "      <th>state</th>\n",
              "      <th>drivetrain</th>\n",
              "      <th>price_usd</th>\n",
              "      <th>is_exchangeable</th>\n",
              "      <th>number_of_photos</th>\n",
              "      <th>up_counter</th>\n",
              "      <th>duration_listed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Subaru</td>\n",
              "      <td>Outback</td>\n",
              "      <td>automatic</td>\n",
              "      <td>silver</td>\n",
              "      <td>190000</td>\n",
              "      <td>2012</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>False</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>2.5</td>\n",
              "      <td>universal</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>all</td>\n",
              "      <td>15260.000</td>\n",
              "      <td>False</td>\n",
              "      <td>4.5</td>\n",
              "      <td>6.5</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Subaru</td>\n",
              "      <td>Outback</td>\n",
              "      <td>automatic</td>\n",
              "      <td>blue</td>\n",
              "      <td>290000</td>\n",
              "      <td>2004</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>False</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>3.0</td>\n",
              "      <td>universal</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>all</td>\n",
              "      <td>7000.000</td>\n",
              "      <td>True</td>\n",
              "      <td>6.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>41.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Subaru</td>\n",
              "      <td>Forester</td>\n",
              "      <td>automatic</td>\n",
              "      <td>red</td>\n",
              "      <td>402000</td>\n",
              "      <td>2003</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>False</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>2.5</td>\n",
              "      <td>suv</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>all</td>\n",
              "      <td>3920.000</td>\n",
              "      <td>True</td>\n",
              "      <td>2.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>75.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Subaru</td>\n",
              "      <td>Impreza</td>\n",
              "      <td>mechanical</td>\n",
              "      <td>blue</td>\n",
              "      <td>10000</td>\n",
              "      <td>2001</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>False</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>3.0</td>\n",
              "      <td>sedan</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>all</td>\n",
              "      <td>13998.600</td>\n",
              "      <td>True</td>\n",
              "      <td>4.5</td>\n",
              "      <td>21.0</td>\n",
              "      <td>43.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Subaru</td>\n",
              "      <td>Legacy</td>\n",
              "      <td>automatic</td>\n",
              "      <td>black</td>\n",
              "      <td>280000</td>\n",
              "      <td>2003</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>False</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>2.5</td>\n",
              "      <td>universal</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>all</td>\n",
              "      <td>2987.754</td>\n",
              "      <td>True</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>3.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38526</th>\n",
              "      <td>Chrysler</td>\n",
              "      <td>300</td>\n",
              "      <td>automatic</td>\n",
              "      <td>silver</td>\n",
              "      <td>290000</td>\n",
              "      <td>2002</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>False</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>3.5</td>\n",
              "      <td>sedan</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>front</td>\n",
              "      <td>3850.000</td>\n",
              "      <td>True</td>\n",
              "      <td>2.5</td>\n",
              "      <td>42.5</td>\n",
              "      <td>150.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38527</th>\n",
              "      <td>Chrysler</td>\n",
              "      <td>PT Cruiser</td>\n",
              "      <td>mechanical</td>\n",
              "      <td>blue</td>\n",
              "      <td>321000</td>\n",
              "      <td>2006</td>\n",
              "      <td>diesel</td>\n",
              "      <td>False</td>\n",
              "      <td>diesel</td>\n",
              "      <td>2.2</td>\n",
              "      <td>hatchback</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>front</td>\n",
              "      <td>6720.000</td>\n",
              "      <td>True</td>\n",
              "      <td>2.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>158.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38528</th>\n",
              "      <td>Chrysler</td>\n",
              "      <td>300</td>\n",
              "      <td>automatic</td>\n",
              "      <td>blue</td>\n",
              "      <td>777957</td>\n",
              "      <td>2002</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>False</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>3.5</td>\n",
              "      <td>sedan</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>front</td>\n",
              "      <td>6020.000</td>\n",
              "      <td>False</td>\n",
              "      <td>1.5</td>\n",
              "      <td>31.5</td>\n",
              "      <td>184.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38529</th>\n",
              "      <td>Chrysler</td>\n",
              "      <td>PT Cruiser</td>\n",
              "      <td>mechanical</td>\n",
              "      <td>black</td>\n",
              "      <td>20000</td>\n",
              "      <td>2003</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>False</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>2.0</td>\n",
              "      <td>minivan</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>front</td>\n",
              "      <td>5600.000</td>\n",
              "      <td>True</td>\n",
              "      <td>3.5</td>\n",
              "      <td>78.0</td>\n",
              "      <td>245.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38530</th>\n",
              "      <td>Chrysler</td>\n",
              "      <td>Voyager</td>\n",
              "      <td>automatic</td>\n",
              "      <td>silver</td>\n",
              "      <td>297729</td>\n",
              "      <td>2002</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>False</td>\n",
              "      <td>gasoline</td>\n",
              "      <td>2.4</td>\n",
              "      <td>minivan</td>\n",
              "      <td>False</td>\n",
              "      <td>owned</td>\n",
              "      <td>front</td>\n",
              "      <td>4480.000</td>\n",
              "      <td>True</td>\n",
              "      <td>2.0</td>\n",
              "      <td>36.5</td>\n",
              "      <td>316.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>38531 rows × 19 columns</p>\n",
              "</div>\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
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              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "          const element = document.querySelector('#df-42d61d17-ba58-441a-98de-f9fe8675e3fd');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
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              "  "
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          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "car = pd.read_csv('cars.csv')\n",
        "car"
      ]
    },
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              "</style>\n",
              "<table id=\"T_86a7b\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_86a7b_level0_col0\" class=\"col_heading level0 col0\" >Description</th>\n",
              "      <th id=\"T_86a7b_level0_col1\" class=\"col_heading level0 col1\" >Value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_86a7b_row0_col0\" class=\"data row0 col0\" >Session id</td>\n",
              "      <td id=\"T_86a7b_row0_col1\" class=\"data row0 col1\" >732</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_86a7b_row1_col0\" class=\"data row1 col0\" >Target</td>\n",
              "      <td id=\"T_86a7b_row1_col1\" class=\"data row1 col1\" >price_usd</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "      <td id=\"T_86a7b_row2_col0\" class=\"data row2 col0\" >Target type</td>\n",
              "      <td id=\"T_86a7b_row2_col1\" class=\"data row2 col1\" >Regression</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_86a7b_row3_col0\" class=\"data row3 col0\" >Original data shape</td>\n",
              "      <td id=\"T_86a7b_row3_col1\" class=\"data row3 col1\" >(38531, 19)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "      <td id=\"T_86a7b_row4_col0\" class=\"data row4 col0\" >Transformed data shape</td>\n",
              "      <td id=\"T_86a7b_row4_col1\" class=\"data row4 col1\" >(38531, 52)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "      <td id=\"T_86a7b_row5_col0\" class=\"data row5 col0\" >Transformed train set shape</td>\n",
              "      <td id=\"T_86a7b_row5_col1\" class=\"data row5 col1\" >(26971, 52)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "      <td id=\"T_86a7b_row6_col0\" class=\"data row6 col0\" >Transformed test set shape</td>\n",
              "      <td id=\"T_86a7b_row6_col1\" class=\"data row6 col1\" >(11560, 52)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "      <td id=\"T_86a7b_row7_col0\" class=\"data row7 col0\" >Ordinal features</td>\n",
              "      <td id=\"T_86a7b_row7_col1\" class=\"data row7 col1\" >1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "      <td id=\"T_86a7b_row8_col0\" class=\"data row8 col0\" >Numeric features</td>\n",
              "      <td id=\"T_86a7b_row8_col1\" class=\"data row8 col1\" >6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "      <td id=\"T_86a7b_row9_col0\" class=\"data row9 col0\" >Categorical features</td>\n",
              "      <td id=\"T_86a7b_row9_col1\" class=\"data row9 col1\" >9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
              "      <td id=\"T_86a7b_row10_col0\" class=\"data row10 col0\" >Rows with missing values</td>\n",
              "      <td id=\"T_86a7b_row10_col1\" class=\"data row10 col1\" >0.0%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
              "      <td id=\"T_86a7b_row11_col0\" class=\"data row11 col0\" >Preprocess</td>\n",
              "      <td id=\"T_86a7b_row11_col1\" class=\"data row11 col1\" >True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
              "      <td id=\"T_86a7b_row12_col0\" class=\"data row12 col0\" >Imputation type</td>\n",
              "      <td id=\"T_86a7b_row12_col1\" class=\"data row12 col1\" >simple</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
              "      <td id=\"T_86a7b_row13_col0\" class=\"data row13 col0\" >Numeric imputation</td>\n",
              "      <td id=\"T_86a7b_row13_col1\" class=\"data row13 col1\" >mean</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
              "      <td id=\"T_86a7b_row14_col0\" class=\"data row14 col0\" >Categorical imputation</td>\n",
              "      <td id=\"T_86a7b_row14_col1\" class=\"data row14 col1\" >mode</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
              "      <td id=\"T_86a7b_row15_col0\" class=\"data row15 col0\" >Maximum one-hot encoding</td>\n",
              "      <td id=\"T_86a7b_row15_col1\" class=\"data row15 col1\" >25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
              "      <td id=\"T_86a7b_row16_col0\" class=\"data row16 col0\" >Encoding method</td>\n",
              "      <td id=\"T_86a7b_row16_col1\" class=\"data row16 col1\" >None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
              "      <td id=\"T_86a7b_row17_col0\" class=\"data row17 col0\" >Fold Generator</td>\n",
              "      <td id=\"T_86a7b_row17_col1\" class=\"data row17 col1\" >KFold</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
              "      <td id=\"T_86a7b_row18_col0\" class=\"data row18 col0\" >Fold Number</td>\n",
              "      <td id=\"T_86a7b_row18_col1\" class=\"data row18 col1\" >10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
              "      <td id=\"T_86a7b_row19_col0\" class=\"data row19 col0\" >CPU Jobs</td>\n",
              "      <td id=\"T_86a7b_row19_col1\" class=\"data row19 col1\" >-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
              "      <td id=\"T_86a7b_row20_col0\" class=\"data row20 col0\" >Use GPU</td>\n",
              "      <td id=\"T_86a7b_row20_col1\" class=\"data row20 col1\" >False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
              "      <td id=\"T_86a7b_row21_col0\" class=\"data row21 col0\" >Log Experiment</td>\n",
              "      <td id=\"T_86a7b_row21_col1\" class=\"data row21 col1\" >False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
              "      <td id=\"T_86a7b_row22_col0\" class=\"data row22 col0\" >Experiment Name</td>\n",
              "      <td id=\"T_86a7b_row22_col1\" class=\"data row22 col1\" >reg-default-name</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_86a7b_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
              "      <td id=\"T_86a7b_row23_col0\" class=\"data row23 col0\" >USI</td>\n",
              "      <td id=\"T_86a7b_row23_col1\" class=\"data row23 col1\" >9d20</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "from pycaret.regression import *\n",
        "s = setup(car, target='price_usd')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
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          "height": 1000,
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            "5e165b79eaef4adda53b487ae1723627",
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        "id": "BNwi_DHYvI8L",
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      "outputs": [
        {
          "output_type": "display_data",
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              "<IPython.core.display.HTML object>"
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              "#T_f3517 th {\n",
              "  text-align: left;\n",
              "}\n",
              "#T_f3517_row0_col0, #T_f3517_row1_col0, #T_f3517_row1_col1, #T_f3517_row1_col2, #T_f3517_row1_col3, #T_f3517_row1_col4, #T_f3517_row1_col5, #T_f3517_row1_col6, #T_f3517_row2_col0, #T_f3517_row2_col1, #T_f3517_row2_col2, #T_f3517_row2_col3, #T_f3517_row2_col4, #T_f3517_row2_col5, #T_f3517_row2_col6, #T_f3517_row3_col0, #T_f3517_row3_col1, #T_f3517_row3_col2, #T_f3517_row3_col3, #T_f3517_row3_col4, #T_f3517_row3_col5, #T_f3517_row3_col6, #T_f3517_row4_col0, #T_f3517_row4_col1, #T_f3517_row4_col2, #T_f3517_row4_col3, #T_f3517_row4_col4, #T_f3517_row4_col5, #T_f3517_row4_col6, #T_f3517_row5_col0, #T_f3517_row5_col1, #T_f3517_row5_col2, #T_f3517_row5_col3, #T_f3517_row5_col4, #T_f3517_row5_col5, #T_f3517_row5_col6, #T_f3517_row6_col0, #T_f3517_row6_col1, #T_f3517_row6_col2, #T_f3517_row6_col3, #T_f3517_row6_col4, #T_f3517_row6_col5, #T_f3517_row6_col6, #T_f3517_row7_col0, #T_f3517_row7_col1, #T_f3517_row7_col2, #T_f3517_row7_col3, #T_f3517_row7_col4, #T_f3517_row7_col5, #T_f3517_row7_col6, #T_f3517_row8_col0, #T_f3517_row8_col1, #T_f3517_row8_col2, #T_f3517_row8_col3, #T_f3517_row8_col4, #T_f3517_row8_col5, #T_f3517_row8_col6, #T_f3517_row9_col0, #T_f3517_row9_col1, #T_f3517_row9_col2, #T_f3517_row9_col3, #T_f3517_row9_col4, #T_f3517_row9_col5, #T_f3517_row9_col6, #T_f3517_row10_col0, #T_f3517_row10_col1, #T_f3517_row10_col2, #T_f3517_row10_col3, #T_f3517_row10_col4, #T_f3517_row10_col5, #T_f3517_row10_col6, #T_f3517_row11_col0, #T_f3517_row11_col1, #T_f3517_row11_col2, #T_f3517_row11_col3, #T_f3517_row11_col4, #T_f3517_row11_col5, #T_f3517_row11_col6, #T_f3517_row12_col0, #T_f3517_row12_col1, #T_f3517_row12_col2, #T_f3517_row12_col3, #T_f3517_row12_col4, #T_f3517_row12_col5, #T_f3517_row12_col6, #T_f3517_row13_col0, #T_f3517_row13_col1, #T_f3517_row13_col2, #T_f3517_row13_col3, #T_f3517_row13_col4, #T_f3517_row13_col5, #T_f3517_row13_col6, #T_f3517_row14_col0, #T_f3517_row14_col1, #T_f3517_row14_col2, #T_f3517_row14_col3, #T_f3517_row14_col4, #T_f3517_row14_col5, #T_f3517_row14_col6, #T_f3517_row15_col0, #T_f3517_row15_col1, #T_f3517_row15_col2, #T_f3517_row15_col3, #T_f3517_row15_col4, #T_f3517_row15_col5, #T_f3517_row15_col6, #T_f3517_row16_col0, #T_f3517_row16_col1, #T_f3517_row16_col2, #T_f3517_row16_col3, #T_f3517_row16_col4, #T_f3517_row16_col5, #T_f3517_row16_col6, #T_f3517_row17_col0, #T_f3517_row17_col1, #T_f3517_row17_col2, #T_f3517_row17_col3, #T_f3517_row17_col4, #T_f3517_row17_col5, #T_f3517_row17_col6, #T_f3517_row18_col0, #T_f3517_row18_col1, #T_f3517_row18_col2, #T_f3517_row18_col3, #T_f3517_row18_col4, #T_f3517_row18_col5, #T_f3517_row18_col6 {\n",
              "  text-align: left;\n",
              "}\n",
              "#T_f3517_row0_col1, #T_f3517_row0_col2, #T_f3517_row0_col3, #T_f3517_row0_col4, #T_f3517_row0_col5, #T_f3517_row0_col6 {\n",
              "  text-align: left;\n",
              "  background-color: yellow;\n",
              "}\n",
              "#T_f3517_row0_col7, #T_f3517_row1_col7, #T_f3517_row2_col7, #T_f3517_row3_col7, #T_f3517_row4_col7, #T_f3517_row5_col7, #T_f3517_row6_col7, #T_f3517_row7_col7, #T_f3517_row8_col7, #T_f3517_row9_col7, #T_f3517_row11_col7, #T_f3517_row12_col7, #T_f3517_row13_col7, #T_f3517_row14_col7, #T_f3517_row15_col7, #T_f3517_row16_col7, #T_f3517_row17_col7, #T_f3517_row18_col7 {\n",
              "  text-align: left;\n",
              "  background-color: lightgrey;\n",
              "}\n",
              "#T_f3517_row10_col7 {\n",
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              "  background-color: lightgrey;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_f3517\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_f3517_level0_col0\" class=\"col_heading level0 col0\" >Model</th>\n",
              "      <th id=\"T_f3517_level0_col1\" class=\"col_heading level0 col1\" >MAE</th>\n",
              "      <th id=\"T_f3517_level0_col2\" class=\"col_heading level0 col2\" >MSE</th>\n",
              "      <th id=\"T_f3517_level0_col3\" class=\"col_heading level0 col3\" >RMSE</th>\n",
              "      <th id=\"T_f3517_level0_col4\" class=\"col_heading level0 col4\" >R2</th>\n",
              "      <th id=\"T_f3517_level0_col5\" class=\"col_heading level0 col5\" >RMSLE</th>\n",
              "      <th id=\"T_f3517_level0_col6\" class=\"col_heading level0 col6\" >MAPE</th>\n",
              "      <th id=\"T_f3517_level0_col7\" class=\"col_heading level0 col7\" >TT (Sec)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row0\" class=\"row_heading level0 row0\" >xgboost</th>\n",
              "      <td id=\"T_f3517_row0_col0\" class=\"data row0 col0\" >Extreme Gradient Boosting</td>\n",
              "      <td id=\"T_f3517_row0_col1\" class=\"data row0 col1\" >1447.1562</td>\n",
              "      <td id=\"T_f3517_row0_col2\" class=\"data row0 col2\" >6211022.3500</td>\n",
              "      <td id=\"T_f3517_row0_col3\" class=\"data row0 col3\" >2487.7375</td>\n",
              "      <td id=\"T_f3517_row0_col4\" class=\"data row0 col4\" >0.9233</td>\n",
              "      <td id=\"T_f3517_row0_col5\" class=\"data row0 col5\" >0.3479</td>\n",
              "      <td id=\"T_f3517_row0_col6\" class=\"data row0 col6\" >0.3508</td>\n",
              "      <td id=\"T_f3517_row0_col7\" class=\"data row0 col7\" >7.1900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row1\" class=\"row_heading level0 row1\" >lightgbm</th>\n",
              "      <td id=\"T_f3517_row1_col0\" class=\"data row1 col0\" >Light Gradient Boosting Machine</td>\n",
              "      <td id=\"T_f3517_row1_col1\" class=\"data row1 col1\" >1519.8957</td>\n",
              "      <td id=\"T_f3517_row1_col2\" class=\"data row1 col2\" >6553602.7125</td>\n",
              "      <td id=\"T_f3517_row1_col3\" class=\"data row1 col3\" >2556.0892</td>\n",
              "      <td id=\"T_f3517_row1_col4\" class=\"data row1 col4\" >0.9190</td>\n",
              "      <td id=\"T_f3517_row1_col5\" class=\"data row1 col5\" >0.3573</td>\n",
              "      <td id=\"T_f3517_row1_col6\" class=\"data row1 col6\" >0.4055</td>\n",
              "      <td id=\"T_f3517_row1_col7\" class=\"data row1 col7\" >1.0680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row2\" class=\"row_heading level0 row2\" >rf</th>\n",
              "      <td id=\"T_f3517_row2_col0\" class=\"data row2 col0\" >Random Forest Regressor</td>\n",
              "      <td id=\"T_f3517_row2_col1\" class=\"data row2 col1\" >1480.8963</td>\n",
              "      <td id=\"T_f3517_row2_col2\" class=\"data row2 col2\" >6892377.1360</td>\n",
              "      <td id=\"T_f3517_row2_col3\" class=\"data row2 col3\" >2622.1790</td>\n",
              "      <td id=\"T_f3517_row2_col4\" class=\"data row2 col4\" >0.9148</td>\n",
              "      <td id=\"T_f3517_row2_col5\" class=\"data row2 col5\" >0.3481</td>\n",
              "      <td id=\"T_f3517_row2_col6\" class=\"data row2 col6\" >0.4389</td>\n",
              "      <td id=\"T_f3517_row2_col7\" class=\"data row2 col7\" >19.7880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row3\" class=\"row_heading level0 row3\" >et</th>\n",
              "      <td id=\"T_f3517_row3_col0\" class=\"data row3 col0\" >Extra Trees Regressor</td>\n",
              "      <td id=\"T_f3517_row3_col1\" class=\"data row3 col1\" >1496.0048</td>\n",
              "      <td id=\"T_f3517_row3_col2\" class=\"data row3 col2\" >6969359.2733</td>\n",
              "      <td id=\"T_f3517_row3_col3\" class=\"data row3 col3\" >2637.6579</td>\n",
              "      <td id=\"T_f3517_row3_col4\" class=\"data row3 col4\" >0.9138</td>\n",
              "      <td id=\"T_f3517_row3_col5\" class=\"data row3 col5\" >0.3493</td>\n",
              "      <td id=\"T_f3517_row3_col6\" class=\"data row3 col6\" >0.4567</td>\n",
              "      <td id=\"T_f3517_row3_col7\" class=\"data row3 col7\" >16.6510</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row4\" class=\"row_heading level0 row4\" >gbr</th>\n",
              "      <td id=\"T_f3517_row4_col0\" class=\"data row4 col0\" >Gradient Boosting Regressor</td>\n",
              "      <td id=\"T_f3517_row4_col1\" class=\"data row4 col1\" >1796.5434</td>\n",
              "      <td id=\"T_f3517_row4_col2\" class=\"data row4 col2\" >8632575.4120</td>\n",
              "      <td id=\"T_f3517_row4_col3\" class=\"data row4 col3\" >2936.0161</td>\n",
              "      <td id=\"T_f3517_row4_col4\" class=\"data row4 col4\" >0.8932</td>\n",
              "      <td id=\"T_f3517_row4_col5\" class=\"data row4 col5\" >0.4010</td>\n",
              "      <td id=\"T_f3517_row4_col6\" class=\"data row4 col6\" >0.4632</td>\n",
              "      <td id=\"T_f3517_row4_col7\" class=\"data row4 col7\" >4.9830</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row5\" class=\"row_heading level0 row5\" >dt</th>\n",
              "      <td id=\"T_f3517_row5_col0\" class=\"data row5 col0\" >Decision Tree Regressor</td>\n",
              "      <td id=\"T_f3517_row5_col1\" class=\"data row5 col1\" >2082.2799</td>\n",
              "      <td id=\"T_f3517_row5_col2\" class=\"data row5 col2\" >13807137.1014</td>\n",
              "      <td id=\"T_f3517_row5_col3\" class=\"data row5 col3\" >3712.1401</td>\n",
              "      <td id=\"T_f3517_row5_col4\" class=\"data row5 col4\" >0.8293</td>\n",
              "      <td id=\"T_f3517_row5_col5\" class=\"data row5 col5\" >0.4641</td>\n",
              "      <td id=\"T_f3517_row5_col6\" class=\"data row5 col6\" >0.5300</td>\n",
              "      <td id=\"T_f3517_row5_col7\" class=\"data row5 col7\" >0.7060</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row6\" class=\"row_heading level0 row6\" >ridge</th>\n",
              "      <td id=\"T_f3517_row6_col0\" class=\"data row6 col0\" >Ridge Regression</td>\n",
              "      <td id=\"T_f3517_row6_col1\" class=\"data row6 col1\" >3034.3672</td>\n",
              "      <td id=\"T_f3517_row6_col2\" class=\"data row6 col2\" >22056473.4111</td>\n",
              "      <td id=\"T_f3517_row6_col3\" class=\"data row6 col3\" >4693.3844</td>\n",
              "      <td id=\"T_f3517_row6_col4\" class=\"data row6 col4\" >0.7271</td>\n",
              "      <td id=\"T_f3517_row6_col5\" class=\"data row6 col5\" >0.7252</td>\n",
              "      <td id=\"T_f3517_row6_col6\" class=\"data row6 col6\" >1.0113</td>\n",
              "      <td id=\"T_f3517_row6_col7\" class=\"data row6 col7\" >0.6880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row7\" class=\"row_heading level0 row7\" >br</th>\n",
              "      <td id=\"T_f3517_row7_col0\" class=\"data row7 col0\" >Bayesian Ridge</td>\n",
              "      <td id=\"T_f3517_row7_col1\" class=\"data row7 col1\" >3034.6405</td>\n",
              "      <td id=\"T_f3517_row7_col2\" class=\"data row7 col2\" >22057235.9813</td>\n",
              "      <td id=\"T_f3517_row7_col3\" class=\"data row7 col3\" >4693.3955</td>\n",
              "      <td id=\"T_f3517_row7_col4\" class=\"data row7 col4\" >0.7271</td>\n",
              "      <td id=\"T_f3517_row7_col5\" class=\"data row7 col5\" >0.7253</td>\n",
              "      <td id=\"T_f3517_row7_col6\" class=\"data row7 col6\" >1.0154</td>\n",
              "      <td id=\"T_f3517_row7_col7\" class=\"data row7 col7\" >0.5720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row8\" class=\"row_heading level0 row8\" >lasso</th>\n",
              "      <td id=\"T_f3517_row8_col0\" class=\"data row8 col0\" >Lasso Regression</td>\n",
              "      <td id=\"T_f3517_row8_col1\" class=\"data row8 col1\" >3033.6386</td>\n",
              "      <td id=\"T_f3517_row8_col2\" class=\"data row8 col2\" >22061057.0630</td>\n",
              "      <td id=\"T_f3517_row8_col3\" class=\"data row8 col3\" >4693.7840</td>\n",
              "      <td id=\"T_f3517_row8_col4\" class=\"data row8 col4\" >0.7270</td>\n",
              "      <td id=\"T_f3517_row8_col5\" class=\"data row8 col5\" >0.7241</td>\n",
              "      <td id=\"T_f3517_row8_col6\" class=\"data row8 col6\" >1.0154</td>\n",
              "      <td id=\"T_f3517_row8_col7\" class=\"data row8 col7\" >1.5830</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row9\" class=\"row_heading level0 row9\" >lr</th>\n",
              "      <td id=\"T_f3517_row9_col0\" class=\"data row9 col0\" >Linear Regression</td>\n",
              "      <td id=\"T_f3517_row9_col1\" class=\"data row9 col1\" >3034.4149</td>\n",
              "      <td id=\"T_f3517_row9_col2\" class=\"data row9 col2\" >22058057.9070</td>\n",
              "      <td id=\"T_f3517_row9_col3\" class=\"data row9 col3\" >4693.5663</td>\n",
              "      <td id=\"T_f3517_row9_col4\" class=\"data row9 col4\" >0.7270</td>\n",
              "      <td id=\"T_f3517_row9_col5\" class=\"data row9 col5\" >0.7250</td>\n",
              "      <td id=\"T_f3517_row9_col6\" class=\"data row9 col6\" >1.0106</td>\n",
              "      <td id=\"T_f3517_row9_col7\" class=\"data row9 col7\" >1.2930</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row10\" class=\"row_heading level0 row10\" >llar</th>\n",
              "      <td id=\"T_f3517_row10_col0\" class=\"data row10 col0\" >Lasso Least Angle Regression</td>\n",
              "      <td id=\"T_f3517_row10_col1\" class=\"data row10 col1\" >3035.7245</td>\n",
              "      <td id=\"T_f3517_row10_col2\" class=\"data row10 col2\" >22088444.5104</td>\n",
              "      <td id=\"T_f3517_row10_col3\" class=\"data row10 col3\" >4696.5923</td>\n",
              "      <td id=\"T_f3517_row10_col4\" class=\"data row10 col4\" >0.7267</td>\n",
              "      <td id=\"T_f3517_row10_col5\" class=\"data row10 col5\" >0.7268</td>\n",
              "      <td id=\"T_f3517_row10_col6\" class=\"data row10 col6\" >1.0361</td>\n",
              "      <td id=\"T_f3517_row10_col7\" class=\"data row10 col7\" >0.4620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row11\" class=\"row_heading level0 row11\" >en</th>\n",
              "      <td id=\"T_f3517_row11_col0\" class=\"data row11 col0\" >Elastic Net</td>\n",
              "      <td id=\"T_f3517_row11_col1\" class=\"data row11 col1\" >3125.8346</td>\n",
              "      <td id=\"T_f3517_row11_col2\" class=\"data row11 col2\" >24149804.2324</td>\n",
              "      <td id=\"T_f3517_row11_col3\" class=\"data row11 col3\" >4909.8974</td>\n",
              "      <td id=\"T_f3517_row11_col4\" class=\"data row11 col4\" >0.7014</td>\n",
              "      <td id=\"T_f3517_row11_col5\" class=\"data row11 col5\" >0.7247</td>\n",
              "      <td id=\"T_f3517_row11_col6\" class=\"data row11 col6\" >1.0657</td>\n",
              "      <td id=\"T_f3517_row11_col7\" class=\"data row11 col7\" >0.5890</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row12\" class=\"row_heading level0 row12\" >omp</th>\n",
              "      <td id=\"T_f3517_row12_col0\" class=\"data row12 col0\" >Orthogonal Matching Pursuit</td>\n",
              "      <td id=\"T_f3517_row12_col1\" class=\"data row12 col1\" >3303.3423</td>\n",
              "      <td id=\"T_f3517_row12_col2\" class=\"data row12 col2\" >27469476.7574</td>\n",
              "      <td id=\"T_f3517_row12_col3\" class=\"data row12 col3\" >5236.0191</td>\n",
              "      <td id=\"T_f3517_row12_col4\" class=\"data row12 col4\" >0.6603</td>\n",
              "      <td id=\"T_f3517_row12_col5\" class=\"data row12 col5\" >0.7164</td>\n",
              "      <td id=\"T_f3517_row12_col6\" class=\"data row12 col6\" >1.0850</td>\n",
              "      <td id=\"T_f3517_row12_col7\" class=\"data row12 col7\" >0.6850</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row13\" class=\"row_heading level0 row13\" >knn</th>\n",
              "      <td id=\"T_f3517_row13_col0\" class=\"data row13 col0\" >K Neighbors Regressor</td>\n",
              "      <td id=\"T_f3517_row13_col1\" class=\"data row13 col1\" >3658.0636</td>\n",
              "      <td id=\"T_f3517_row13_col2\" class=\"data row13 col2\" >32655865.8000</td>\n",
              "      <td id=\"T_f3517_row13_col3\" class=\"data row13 col3\" >5709.7555</td>\n",
              "      <td id=\"T_f3517_row13_col4\" class=\"data row13 col4\" >0.5961</td>\n",
              "      <td id=\"T_f3517_row13_col5\" class=\"data row13 col5\" >0.6841</td>\n",
              "      <td id=\"T_f3517_row13_col6\" class=\"data row13 col6\" >1.0265</td>\n",
              "      <td id=\"T_f3517_row13_col7\" class=\"data row13 col7\" >1.0530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row14\" class=\"row_heading level0 row14\" >huber</th>\n",
              "      <td id=\"T_f3517_row14_col0\" class=\"data row14 col0\" >Huber Regressor</td>\n",
              "      <td id=\"T_f3517_row14_col1\" class=\"data row14 col1\" >3927.5342</td>\n",
              "      <td id=\"T_f3517_row14_col2\" class=\"data row14 col2\" >39323969.7382</td>\n",
              "      <td id=\"T_f3517_row14_col3\" class=\"data row14 col3\" >6266.7302</td>\n",
              "      <td id=\"T_f3517_row14_col4\" class=\"data row14 col4\" >0.5136</td>\n",
              "      <td id=\"T_f3517_row14_col5\" class=\"data row14 col5\" >0.8062</td>\n",
              "      <td id=\"T_f3517_row14_col6\" class=\"data row14 col6\" >1.2196</td>\n",
              "      <td id=\"T_f3517_row14_col7\" class=\"data row14 col7\" >0.8610</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row15\" class=\"row_heading level0 row15\" >ada</th>\n",
              "      <td id=\"T_f3517_row15_col0\" class=\"data row15 col0\" >AdaBoost Regressor</td>\n",
              "      <td id=\"T_f3517_row15_col1\" class=\"data row15 col1\" >6169.0319</td>\n",
              "      <td id=\"T_f3517_row15_col2\" class=\"data row15 col2\" >47342044.1858</td>\n",
              "      <td id=\"T_f3517_row15_col3\" class=\"data row15 col3\" >6878.3493</td>\n",
              "      <td id=\"T_f3517_row15_col4\" class=\"data row15 col4\" >0.4131</td>\n",
              "      <td id=\"T_f3517_row15_col5\" class=\"data row15 col5\" >1.1097</td>\n",
              "      <td id=\"T_f3517_row15_col6\" class=\"data row15 col6\" >3.1094</td>\n",
              "      <td id=\"T_f3517_row15_col7\" class=\"data row15 col7\" >3.2190</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row16\" class=\"row_heading level0 row16\" >dummy</th>\n",
              "      <td id=\"T_f3517_row16_col0\" class=\"data row16 col0\" >Dummy Regressor</td>\n",
              "      <td id=\"T_f3517_row16_col1\" class=\"data row16 col1\" >6457.8144</td>\n",
              "      <td id=\"T_f3517_row16_col2\" class=\"data row16 col2\" >80927218.4000</td>\n",
              "      <td id=\"T_f3517_row16_col3\" class=\"data row16 col3\" >8991.3696</td>\n",
              "      <td id=\"T_f3517_row16_col4\" class=\"data row16 col4\" >-0.0005</td>\n",
              "      <td id=\"T_f3517_row16_col5\" class=\"data row16 col5\" >1.1195</td>\n",
              "      <td id=\"T_f3517_row16_col6\" class=\"data row16 col6\" >2.9854</td>\n",
              "      <td id=\"T_f3517_row16_col7\" class=\"data row16 col7\" >0.5760</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row17\" class=\"row_heading level0 row17\" >par</th>\n",
              "      <td id=\"T_f3517_row17_col0\" class=\"data row17 col0\" >Passive Aggressive Regressor</td>\n",
              "      <td id=\"T_f3517_row17_col1\" class=\"data row17 col1\" >11671.4303</td>\n",
              "      <td id=\"T_f3517_row17_col2\" class=\"data row17 col2\" >322901329.0023</td>\n",
              "      <td id=\"T_f3517_row17_col3\" class=\"data row17 col3\" >14941.4041</td>\n",
              "      <td id=\"T_f3517_row17_col4\" class=\"data row17 col4\" >-2.9338</td>\n",
              "      <td id=\"T_f3517_row17_col5\" class=\"data row17 col5\" >1.3028</td>\n",
              "      <td id=\"T_f3517_row17_col6\" class=\"data row17 col6\" >6.2148</td>\n",
              "      <td id=\"T_f3517_row17_col7\" class=\"data row17 col7\" >0.5820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_f3517_level0_row18\" class=\"row_heading level0 row18\" >lar</th>\n",
              "      <td id=\"T_f3517_row18_col0\" class=\"data row18 col0\" >Least Angle Regression</td>\n",
              "      <td id=\"T_f3517_row18_col1\" class=\"data row18 col1\" >39714095949.8580</td>\n",
              "      <td id=\"T_f3517_row18_col2\" class=\"data row18 col2\" >41956125483713618398674944.0000</td>\n",
              "      <td id=\"T_f3517_row18_col3\" class=\"data row18 col3\" >2050541140978.8059</td>\n",
              "      <td id=\"T_f3517_row18_col4\" class=\"data row18 col4\" >-527763477108045120.0000</td>\n",
              "      <td id=\"T_f3517_row18_col5\" class=\"data row18 col5\" >2.5891</td>\n",
              "      <td id=\"T_f3517_row18_col6\" class=\"data row18 col6\" >70604536.0501</td>\n",
              "      <td id=\"T_f3517_row18_col7\" class=\"data row18 col7\" >0.7590</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Processing:   0%|          | 0/81 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4e229f88f3704b649ec2bac2918054f7"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/b3e629b1971e1542/manager.min.js"
                }
              }
            }
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": []
          },
          "metadata": {}
        }
      ],
      "source": [
        "best = compare_models()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HW5utstWvJUs",
        "outputId": "85b112b9-b898-40fc-90c9-ec796b508b1c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "XGBRegressor(base_score=None, booster='gbtree', callbacks=None,\n",
            "             colsample_bylevel=None, colsample_bynode=None,\n",
            "             colsample_bytree=None, early_stopping_rounds=None,\n",
            "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
            "             gamma=None, gpu_id=None, grow_policy=None, importance_type=None,\n",
            "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
            "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
            "             max_delta_step=None, max_depth=None, max_leaves=None,\n",
            "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
            "             n_estimators=100, n_jobs=-1, num_parallel_tree=None,\n",
            "             predictor=None, random_state=732, ...)\n"
          ]
        }
      ],
      "source": [
        "print(best)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Classification"
      ],
      "metadata": {
        "id": "yqi7bSGyDC5G"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Load Data"
      ],
      "metadata": {
        "id": "f_nR7OmNDGkT"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 548
        },
        "id": "vQmb69AvtmEq",
        "outputId": "dcf59e7d-7084-4d35-fc41-867de1228175"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   PassengerId  Survived  Pclass  \\\n",
              "0            1         0       3   \n",
              "1            2         1       1   \n",
              "2            3         1       3   \n",
              "3            4         1       1   \n",
              "4            5         0       3   \n",
              "\n",
              "                                                Name     Sex   Age  SibSp  \\\n",
              "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
              "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
              "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
              "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
              "4                           Allen, Mr. William Henry    male  35.0      0   \n",
              "\n",
              "   Parch            Ticket     Fare Cabin Embarked  \n",
              "0      0         A/5 21171   7.2500   NaN        S  \n",
              "1      0          PC 17599  71.2833   C85        C  \n",
              "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
              "3      0            113803  53.1000  C123        S  \n",
              "4      0            373450   8.0500   NaN        S  "
            ],
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              "      <div>\n",
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              "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
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              "      <td>38.0</td>\n",
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              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>Heikkinen, Miss. Laina</td>\n",
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              "      <td>26.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>STON/O2. 3101282</td>\n",
              "      <td>7.9250</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
              "      <td>female</td>\n",
              "      <td>35.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "      <td>53.1000</td>\n",
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              "      <td>S</td>\n",
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              "      <th>4</th>\n",
              "      <td>5</td>\n",
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              "      <td>3</td>\n",
              "      <td>Allen, Mr. William Henry</td>\n",
              "      <td>male</td>\n",
              "      <td>35.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>373450</td>\n",
              "      <td>8.0500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9486d0ee-d3b3-4663-b928-041fe6520cf5')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
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              "\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",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-9486d0ee-d3b3-4663-b928-041fe6520cf5 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-9486d0ee-d3b3-4663-b928-041fe6520cf5');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "import pandas as pd\n",
        "\n",
        "titanic = pd.read_csv('titanic.csv')\n",
        "titanic.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 802
        },
        "id": "7lFIEbK_tma9",
        "outputId": "09077e1f-e2ee-480e-c69a-162c76a2dec2"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f729ef3e3b0>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_e825e_row11_col1 {\n",
              "  background-color: lightgreen;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_e825e\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_e825e_level0_col0\" class=\"col_heading level0 col0\" >Description</th>\n",
              "      <th id=\"T_e825e_level0_col1\" class=\"col_heading level0 col1\" >Value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_e825e_row0_col0\" class=\"data row0 col0\" >Session id</td>\n",
              "      <td id=\"T_e825e_row0_col1\" class=\"data row0 col1\" >2566</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_e825e_row1_col0\" class=\"data row1 col0\" >Target</td>\n",
              "      <td id=\"T_e825e_row1_col1\" class=\"data row1 col1\" >Survived</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "      <td id=\"T_e825e_row2_col0\" class=\"data row2 col0\" >Target type</td>\n",
              "      <td id=\"T_e825e_row2_col1\" class=\"data row2 col1\" >Binary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_e825e_row3_col0\" class=\"data row3 col0\" >Original data shape</td>\n",
              "      <td id=\"T_e825e_row3_col1\" class=\"data row3 col1\" >(891, 12)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "      <td id=\"T_e825e_row4_col0\" class=\"data row4 col0\" >Transformed data shape</td>\n",
              "      <td id=\"T_e825e_row4_col1\" class=\"data row4 col1\" >(891, 14)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "      <td id=\"T_e825e_row5_col0\" class=\"data row5 col0\" >Transformed train set shape</td>\n",
              "      <td id=\"T_e825e_row5_col1\" class=\"data row5 col1\" >(623, 14)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "      <td id=\"T_e825e_row6_col0\" class=\"data row6 col0\" >Transformed test set shape</td>\n",
              "      <td id=\"T_e825e_row6_col1\" class=\"data row6 col1\" >(268, 14)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "      <td id=\"T_e825e_row7_col0\" class=\"data row7 col0\" >Ordinal features</td>\n",
              "      <td id=\"T_e825e_row7_col1\" class=\"data row7 col1\" >1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "      <td id=\"T_e825e_row8_col0\" class=\"data row8 col0\" >Numeric features</td>\n",
              "      <td id=\"T_e825e_row8_col1\" class=\"data row8 col1\" >6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "      <td id=\"T_e825e_row9_col0\" class=\"data row9 col0\" >Categorical features</td>\n",
              "      <td id=\"T_e825e_row9_col1\" class=\"data row9 col1\" >5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
              "      <td id=\"T_e825e_row10_col0\" class=\"data row10 col0\" >Rows with missing values</td>\n",
              "      <td id=\"T_e825e_row10_col1\" class=\"data row10 col1\" >79.5%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
              "      <td id=\"T_e825e_row11_col0\" class=\"data row11 col0\" >Preprocess</td>\n",
              "      <td id=\"T_e825e_row11_col1\" class=\"data row11 col1\" >True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
              "      <td id=\"T_e825e_row12_col0\" class=\"data row12 col0\" >Imputation type</td>\n",
              "      <td id=\"T_e825e_row12_col1\" class=\"data row12 col1\" >simple</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
              "      <td id=\"T_e825e_row13_col0\" class=\"data row13 col0\" >Numeric imputation</td>\n",
              "      <td id=\"T_e825e_row13_col1\" class=\"data row13 col1\" >mean</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
              "      <td id=\"T_e825e_row14_col0\" class=\"data row14 col0\" >Categorical imputation</td>\n",
              "      <td id=\"T_e825e_row14_col1\" class=\"data row14 col1\" >mode</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
              "      <td id=\"T_e825e_row15_col0\" class=\"data row15 col0\" >Maximum one-hot encoding</td>\n",
              "      <td id=\"T_e825e_row15_col1\" class=\"data row15 col1\" >25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
              "      <td id=\"T_e825e_row16_col0\" class=\"data row16 col0\" >Encoding method</td>\n",
              "      <td id=\"T_e825e_row16_col1\" class=\"data row16 col1\" >None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
              "      <td id=\"T_e825e_row17_col0\" class=\"data row17 col0\" >Fold Generator</td>\n",
              "      <td id=\"T_e825e_row17_col1\" class=\"data row17 col1\" >StratifiedKFold</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
              "      <td id=\"T_e825e_row18_col0\" class=\"data row18 col0\" >Fold Number</td>\n",
              "      <td id=\"T_e825e_row18_col1\" class=\"data row18 col1\" >10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
              "      <td id=\"T_e825e_row19_col0\" class=\"data row19 col0\" >CPU Jobs</td>\n",
              "      <td id=\"T_e825e_row19_col1\" class=\"data row19 col1\" >-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
              "      <td id=\"T_e825e_row20_col0\" class=\"data row20 col0\" >Use GPU</td>\n",
              "      <td id=\"T_e825e_row20_col1\" class=\"data row20 col1\" >False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
              "      <td id=\"T_e825e_row21_col0\" class=\"data row21 col0\" >Log Experiment</td>\n",
              "      <td id=\"T_e825e_row21_col1\" class=\"data row21 col1\" >False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
              "      <td id=\"T_e825e_row22_col0\" class=\"data row22 col0\" >Experiment Name</td>\n",
              "      <td id=\"T_e825e_row22_col1\" class=\"data row22 col1\" >clf-default-name</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_e825e_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
              "      <td id=\"T_e825e_row23_col0\" class=\"data row23 col0\" >USI</td>\n",
              "      <td id=\"T_e825e_row23_col1\" class=\"data row23 col1\" >ddd8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "from pycaret.classification import *\n",
        "s = setup(titanic, target='Survived')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Train & Evaluate"
      ],
      "metadata": {
        "id": "9A5_75AmDLXk"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 991,
          "referenced_widgets": [
            "4517987de57d4004873cb39a2babb8b4",
            "7ef4cd26e7f5451095c07cc6b2b0dde9",
            "311c70c943054593a31d3c410f025abf",
            "69ce0ebc66574272abdb526cb0089c69",
            "f3d66e211c654479bab2132f8fff4509",
            "7621829533424724b3b7ea293915670f",
            "c1e7226440c942148c5894a849d4671c",
            "ccd4295639c34483af55df4f7226fa65",
            "2ee4858aae634077aab0074e8a06bf84",
            "db05307952be47b6aba52a8a9530ee37",
            "39eb981770524ab596af277b17431f26"
          ]
        },
        "id": "ptJI7SCVtm1m",
        "outputId": "fe399241-557b-4b3d-c2d4-5138881a261a"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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            "text/html": []
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          "data": {
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              "#T_4fdea_row0_col1, #T_4fdea_row0_col2, #T_4fdea_row0_col3, #T_4fdea_row0_col5, #T_4fdea_row0_col6, #T_4fdea_row0_col7, #T_4fdea_row1_col4 {\n",
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              "#T_4fdea_row0_col8, #T_4fdea_row1_col8, #T_4fdea_row2_col8, #T_4fdea_row3_col8, #T_4fdea_row4_col8, #T_4fdea_row5_col8, #T_4fdea_row6_col8, #T_4fdea_row7_col8, #T_4fdea_row8_col8, #T_4fdea_row9_col8, #T_4fdea_row10_col8, #T_4fdea_row11_col8, #T_4fdea_row12_col8, #T_4fdea_row13_col8 {\n",
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              "</style>\n",
              "<table id=\"T_4fdea\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_4fdea_level0_col0\" class=\"col_heading level0 col0\" >Model</th>\n",
              "      <th id=\"T_4fdea_level0_col1\" class=\"col_heading level0 col1\" >Accuracy</th>\n",
              "      <th id=\"T_4fdea_level0_col2\" class=\"col_heading level0 col2\" >AUC</th>\n",
              "      <th id=\"T_4fdea_level0_col3\" class=\"col_heading level0 col3\" >Recall</th>\n",
              "      <th id=\"T_4fdea_level0_col4\" class=\"col_heading level0 col4\" >Prec.</th>\n",
              "      <th id=\"T_4fdea_level0_col5\" class=\"col_heading level0 col5\" >F1</th>\n",
              "      <th id=\"T_4fdea_level0_col6\" class=\"col_heading level0 col6\" >Kappa</th>\n",
              "      <th id=\"T_4fdea_level0_col7\" class=\"col_heading level0 col7\" >MCC</th>\n",
              "      <th id=\"T_4fdea_level0_col8\" class=\"col_heading level0 col8\" >TT (Sec)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row0\" class=\"row_heading level0 row0\" >lr</th>\n",
              "      <td id=\"T_4fdea_row0_col0\" class=\"data row0 col0\" >Logistic Regression</td>\n",
              "      <td id=\"T_4fdea_row0_col1\" class=\"data row0 col1\" >0.8282</td>\n",
              "      <td id=\"T_4fdea_row0_col2\" class=\"data row0 col2\" >0.8640</td>\n",
              "      <td id=\"T_4fdea_row0_col3\" class=\"data row0 col3\" >0.7192</td>\n",
              "      <td id=\"T_4fdea_row0_col4\" class=\"data row0 col4\" >0.8187</td>\n",
              "      <td id=\"T_4fdea_row0_col5\" class=\"data row0 col5\" >0.7593</td>\n",
              "      <td id=\"T_4fdea_row0_col6\" class=\"data row0 col6\" >0.6273</td>\n",
              "      <td id=\"T_4fdea_row0_col7\" class=\"data row0 col7\" >0.6360</td>\n",
              "      <td id=\"T_4fdea_row0_col8\" class=\"data row0 col8\" >0.7250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row1\" class=\"row_heading level0 row1\" >ridge</th>\n",
              "      <td id=\"T_4fdea_row1_col0\" class=\"data row1 col0\" >Ridge Classifier</td>\n",
              "      <td id=\"T_4fdea_row1_col1\" class=\"data row1 col1\" >0.7561</td>\n",
              "      <td id=\"T_4fdea_row1_col2\" class=\"data row1 col2\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row1_col3\" class=\"data row1 col3\" >0.4391</td>\n",
              "      <td id=\"T_4fdea_row1_col4\" class=\"data row1 col4\" >0.8634</td>\n",
              "      <td id=\"T_4fdea_row1_col5\" class=\"data row1 col5\" >0.5797</td>\n",
              "      <td id=\"T_4fdea_row1_col6\" class=\"data row1 col6\" >0.4322</td>\n",
              "      <td id=\"T_4fdea_row1_col7\" class=\"data row1 col7\" >0.4828</td>\n",
              "      <td id=\"T_4fdea_row1_col8\" class=\"data row1 col8\" >0.4890</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row2\" class=\"row_heading level0 row2\" >et</th>\n",
              "      <td id=\"T_4fdea_row2_col0\" class=\"data row2 col0\" >Extra Trees Classifier</td>\n",
              "      <td id=\"T_4fdea_row2_col1\" class=\"data row2 col1\" >0.7256</td>\n",
              "      <td id=\"T_4fdea_row2_col2\" class=\"data row2 col2\" >0.7479</td>\n",
              "      <td id=\"T_4fdea_row2_col3\" class=\"data row2 col3\" >0.4014</td>\n",
              "      <td id=\"T_4fdea_row2_col4\" class=\"data row2 col4\" >0.7838</td>\n",
              "      <td id=\"T_4fdea_row2_col5\" class=\"data row2 col5\" >0.5198</td>\n",
              "      <td id=\"T_4fdea_row2_col6\" class=\"data row2 col6\" >0.3595</td>\n",
              "      <td id=\"T_4fdea_row2_col7\" class=\"data row2 col7\" >0.4028</td>\n",
              "      <td id=\"T_4fdea_row2_col8\" class=\"data row2 col8\" >0.7610</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row3\" class=\"row_heading level0 row3\" >nb</th>\n",
              "      <td id=\"T_4fdea_row3_col0\" class=\"data row3 col0\" >Naive Bayes</td>\n",
              "      <td id=\"T_4fdea_row3_col1\" class=\"data row3 col1\" >0.6502</td>\n",
              "      <td id=\"T_4fdea_row3_col2\" class=\"data row3 col2\" >0.7949</td>\n",
              "      <td id=\"T_4fdea_row3_col3\" class=\"data row3 col3\" >0.1299</td>\n",
              "      <td id=\"T_4fdea_row3_col4\" class=\"data row3 col4\" >0.7214</td>\n",
              "      <td id=\"T_4fdea_row3_col5\" class=\"data row3 col5\" >0.2155</td>\n",
              "      <td id=\"T_4fdea_row3_col6\" class=\"data row3 col6\" >0.1226</td>\n",
              "      <td id=\"T_4fdea_row3_col7\" class=\"data row3 col7\" >0.2012</td>\n",
              "      <td id=\"T_4fdea_row3_col8\" class=\"data row3 col8\" >0.6110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row4\" class=\"row_heading level0 row4\" >knn</th>\n",
              "      <td id=\"T_4fdea_row4_col0\" class=\"data row4 col0\" >K Neighbors Classifier</td>\n",
              "      <td id=\"T_4fdea_row4_col1\" class=\"data row4 col1\" >0.6487</td>\n",
              "      <td id=\"T_4fdea_row4_col2\" class=\"data row4 col2\" >0.6221</td>\n",
              "      <td id=\"T_4fdea_row4_col3\" class=\"data row4 col3\" >0.3808</td>\n",
              "      <td id=\"T_4fdea_row4_col4\" class=\"data row4 col4\" >0.5706</td>\n",
              "      <td id=\"T_4fdea_row4_col5\" class=\"data row4 col5\" >0.4547</td>\n",
              "      <td id=\"T_4fdea_row4_col6\" class=\"data row4 col6\" >0.2098</td>\n",
              "      <td id=\"T_4fdea_row4_col7\" class=\"data row4 col7\" >0.2210</td>\n",
              "      <td id=\"T_4fdea_row4_col8\" class=\"data row4 col8\" >0.5130</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row5\" class=\"row_heading level0 row5\" >rf</th>\n",
              "      <td id=\"T_4fdea_row5_col0\" class=\"data row5 col0\" >Random Forest Classifier</td>\n",
              "      <td id=\"T_4fdea_row5_col1\" class=\"data row5 col1\" >0.6453</td>\n",
              "      <td id=\"T_4fdea_row5_col2\" class=\"data row5 col2\" >0.8060</td>\n",
              "      <td id=\"T_4fdea_row5_col3\" class=\"data row5 col3\" >0.0966</td>\n",
              "      <td id=\"T_4fdea_row5_col4\" class=\"data row5 col4\" >0.6833</td>\n",
              "      <td id=\"T_4fdea_row5_col5\" class=\"data row5 col5\" >0.1649</td>\n",
              "      <td id=\"T_4fdea_row5_col6\" class=\"data row5 col6\" >0.0990</td>\n",
              "      <td id=\"T_4fdea_row5_col7\" class=\"data row5 col7\" >0.1765</td>\n",
              "      <td id=\"T_4fdea_row5_col8\" class=\"data row5 col8\" >0.8780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row6\" class=\"row_heading level0 row6\" >lda</th>\n",
              "      <td id=\"T_4fdea_row6_col0\" class=\"data row6 col0\" >Linear Discriminant Analysis</td>\n",
              "      <td id=\"T_4fdea_row6_col1\" class=\"data row6 col1\" >0.6244</td>\n",
              "      <td id=\"T_4fdea_row6_col2\" class=\"data row6 col2\" >0.5261</td>\n",
              "      <td id=\"T_4fdea_row6_col3\" class=\"data row6 col3\" >0.0304</td>\n",
              "      <td id=\"T_4fdea_row6_col4\" class=\"data row6 col4\" >0.0778</td>\n",
              "      <td id=\"T_4fdea_row6_col5\" class=\"data row6 col5\" >0.0438</td>\n",
              "      <td id=\"T_4fdea_row6_col6\" class=\"data row6 col6\" >0.0289</td>\n",
              "      <td id=\"T_4fdea_row6_col7\" class=\"data row6 col7\" >0.0347</td>\n",
              "      <td id=\"T_4fdea_row6_col8\" class=\"data row6 col8\" >0.6150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row7\" class=\"row_heading level0 row7\" >dt</th>\n",
              "      <td id=\"T_4fdea_row7_col0\" class=\"data row7 col0\" >Decision Tree Classifier</td>\n",
              "      <td id=\"T_4fdea_row7_col1\" class=\"data row7 col1\" >0.6164</td>\n",
              "      <td id=\"T_4fdea_row7_col2\" class=\"data row7 col2\" >0.5000</td>\n",
              "      <td id=\"T_4fdea_row7_col3\" class=\"data row7 col3\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row7_col4\" class=\"data row7 col4\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row7_col5\" class=\"data row7 col5\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row7_col6\" class=\"data row7 col6\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row7_col7\" class=\"data row7 col7\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row7_col8\" class=\"data row7 col8\" >0.3760</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row8\" class=\"row_heading level0 row8\" >ada</th>\n",
              "      <td id=\"T_4fdea_row8_col0\" class=\"data row8 col0\" >Ada Boost Classifier</td>\n",
              "      <td id=\"T_4fdea_row8_col1\" class=\"data row8 col1\" >0.6164</td>\n",
              "      <td id=\"T_4fdea_row8_col2\" class=\"data row8 col2\" >0.5000</td>\n",
              "      <td id=\"T_4fdea_row8_col3\" class=\"data row8 col3\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row8_col4\" class=\"data row8 col4\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row8_col5\" class=\"data row8 col5\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row8_col6\" class=\"data row8 col6\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row8_col7\" class=\"data row8 col7\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row8_col8\" class=\"data row8 col8\" >0.5280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row9\" class=\"row_heading level0 row9\" >gbc</th>\n",
              "      <td id=\"T_4fdea_row9_col0\" class=\"data row9 col0\" >Gradient Boosting Classifier</td>\n",
              "      <td id=\"T_4fdea_row9_col1\" class=\"data row9 col1\" >0.6164</td>\n",
              "      <td id=\"T_4fdea_row9_col2\" class=\"data row9 col2\" >0.5000</td>\n",
              "      <td id=\"T_4fdea_row9_col3\" class=\"data row9 col3\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row9_col4\" class=\"data row9 col4\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row9_col5\" class=\"data row9 col5\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row9_col6\" class=\"data row9 col6\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row9_col7\" class=\"data row9 col7\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row9_col8\" class=\"data row9 col8\" >0.8390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row10\" class=\"row_heading level0 row10\" >xgboost</th>\n",
              "      <td id=\"T_4fdea_row10_col0\" class=\"data row10 col0\" >Extreme Gradient Boosting</td>\n",
              "      <td id=\"T_4fdea_row10_col1\" class=\"data row10 col1\" >0.6164</td>\n",
              "      <td id=\"T_4fdea_row10_col2\" class=\"data row10 col2\" >0.6640</td>\n",
              "      <td id=\"T_4fdea_row10_col3\" class=\"data row10 col3\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row10_col4\" class=\"data row10 col4\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row10_col5\" class=\"data row10 col5\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row10_col6\" class=\"data row10 col6\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row10_col7\" class=\"data row10 col7\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row10_col8\" class=\"data row10 col8\" >0.6660</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row11\" class=\"row_heading level0 row11\" >lightgbm</th>\n",
              "      <td id=\"T_4fdea_row11_col0\" class=\"data row11 col0\" >Light Gradient Boosting Machine</td>\n",
              "      <td id=\"T_4fdea_row11_col1\" class=\"data row11 col1\" >0.6164</td>\n",
              "      <td id=\"T_4fdea_row11_col2\" class=\"data row11 col2\" >0.5279</td>\n",
              "      <td id=\"T_4fdea_row11_col3\" class=\"data row11 col3\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row11_col4\" class=\"data row11 col4\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row11_col5\" class=\"data row11 col5\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row11_col6\" class=\"data row11 col6\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row11_col7\" class=\"data row11 col7\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row11_col8\" class=\"data row11 col8\" >0.4040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row12\" class=\"row_heading level0 row12\" >dummy</th>\n",
              "      <td id=\"T_4fdea_row12_col0\" class=\"data row12 col0\" >Dummy Classifier</td>\n",
              "      <td id=\"T_4fdea_row12_col1\" class=\"data row12 col1\" >0.6164</td>\n",
              "      <td id=\"T_4fdea_row12_col2\" class=\"data row12 col2\" >0.5000</td>\n",
              "      <td id=\"T_4fdea_row12_col3\" class=\"data row12 col3\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row12_col4\" class=\"data row12 col4\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row12_col5\" class=\"data row12 col5\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row12_col6\" class=\"data row12 col6\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row12_col7\" class=\"data row12 col7\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row12_col8\" class=\"data row12 col8\" >0.3790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row13\" class=\"row_heading level0 row13\" >qda</th>\n",
              "      <td id=\"T_4fdea_row13_col0\" class=\"data row13 col0\" >Quadratic Discriminant Analysis</td>\n",
              "      <td id=\"T_4fdea_row13_col1\" class=\"data row13 col1\" >0.5906</td>\n",
              "      <td id=\"T_4fdea_row13_col2\" class=\"data row13 col2\" >0.5000</td>\n",
              "      <td id=\"T_4fdea_row13_col3\" class=\"data row13 col3\" >0.1000</td>\n",
              "      <td id=\"T_4fdea_row13_col4\" class=\"data row13 col4\" >0.0371</td>\n",
              "      <td id=\"T_4fdea_row13_col5\" class=\"data row13 col5\" >0.0541</td>\n",
              "      <td id=\"T_4fdea_row13_col6\" class=\"data row13 col6\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row13_col7\" class=\"data row13 col7\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row13_col8\" class=\"data row13 col8\" >0.4600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_4fdea_level0_row14\" class=\"row_heading level0 row14\" >svm</th>\n",
              "      <td id=\"T_4fdea_row14_col0\" class=\"data row14 col0\" >SVM - Linear Kernel</td>\n",
              "      <td id=\"T_4fdea_row14_col1\" class=\"data row14 col1\" >0.4928</td>\n",
              "      <td id=\"T_4fdea_row14_col2\" class=\"data row14 col2\" >0.0000</td>\n",
              "      <td id=\"T_4fdea_row14_col3\" class=\"data row14 col3\" >0.6795</td>\n",
              "      <td id=\"T_4fdea_row14_col4\" class=\"data row14 col4\" >0.4777</td>\n",
              "      <td id=\"T_4fdea_row14_col5\" class=\"data row14 col5\" >0.4522</td>\n",
              "      <td id=\"T_4fdea_row14_col6\" class=\"data row14 col6\" >0.0565</td>\n",
              "      <td id=\"T_4fdea_row14_col7\" class=\"data row14 col7\" >0.0727</td>\n",
              "      <td id=\"T_4fdea_row14_col8\" class=\"data row14 col8\" >0.3540</td>\n",
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              "  </tbody>\n",
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              "Processing:   0%|          | 0/65 [00:00<?, ?it/s]"
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        "best = compare_models()"
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        "id": "LTGUl0aptnMx",
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          "text": [
            "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
            "                   intercept_scaling=1, l1_ratio=None, max_iter=1000,\n",
            "                   multi_class='auto', n_jobs=None, penalty='l2',\n",
            "                   random_state=2566, solver='lbfgs', tol=0.0001, verbose=0,\n",
            "                   warm_start=False)\n"
          ]
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        "print(best)"
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    }
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