CAR_PRICE_PREDICTION.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# **CAR PRICE PREDICTION WITH MACHINE LEARNING**"
      ],
      "metadata": {
        "id": "p-B_snWZCcVS"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![09.jpg](data:image/jpeg;base64,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)"
      ],
      "metadata": {
        "id": "pKBW5fi8DY2c"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qX7F0BYyCJCg"
      },
      "source": [
        "\n",
        "Download **Dataset here [CAR PRICE PREDICTION](https://drive.google.com/file/d/1EUfj25s3IVVe4Kxrz1hmf9QCSzy_G6Dh/view?usp=share_link)**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gqVmgmxgylHi"
      },
      "source": [
        "### Knowing about the Dataset"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R6xjm571tdTE"
      },
      "source": [
        "**Importing the Required Libraries**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 83,
      "metadata": {
        "id": "XpO7v5pKAsHK"
      },
      "outputs": [],
      "source": [
        "# Numpy Library for Numerical Calculations\n",
        "import numpy as np\n",
        "\n",
        "# Pandas Library for Dataframe\n",
        "import pandas as pd\n",
        "\n",
        "# Math Library for Mathematical Calulations\n",
        "import math\n",
        "\n",
        "# Pickle Library for Saving the Model\n",
        "import pickle\n",
        "\n",
        "# Matplotlib and Seaborn for Plottings\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# Train_Test_Split for splitting the Dataset\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "# Linear Regression, Decision Tree are Models\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.tree import DecisionTreeRegressor\n",
        "\n",
        "# Mean Absolute Error, R2 Score and Mean Squared Error is for Analysis of Models\n",
        "from sklearn.metrics import mean_absolute_error, r2_score, mean_squared_error\n",
        "from sklearn.metrics import accuracy_score"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LoOr0v_SETRN",
        "outputId": "f11488b0-367b-49d1-9412-a0b8f237e14b"
      },
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xu7WlNl7vbXx"
      },
      "source": [
        "**Reading informations in the Dataset**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 85,
      "metadata": {
        "id": "DpR2bcF-EgC7"
      },
      "outputs": [],
      "source": [
        "car_price = pd.read_csv(\"/content/drive/MyDrive/Oasis Infobyte/Data Science - Internship/Car-Price-Prediction/CarPrice.csv\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ztslY5yawK3r"
      },
      "source": [
        "**Checking for null values in Data**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 86,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cNIKxwxSFP4J",
        "outputId": "95ec0810-031b-4144-b26d-3fe811023727"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "car_ID              0\n",
              "symboling           0\n",
              "CarName             0\n",
              "fueltype            0\n",
              "aspiration          0\n",
              "doornumber          0\n",
              "carbody             0\n",
              "drivewheel          0\n",
              "enginelocation      0\n",
              "wheelbase           0\n",
              "carlength           0\n",
              "carwidth            0\n",
              "carheight           0\n",
              "curbweight          0\n",
              "enginetype          0\n",
              "cylindernumber      0\n",
              "enginesize          0\n",
              "fuelsystem          0\n",
              "boreratio           0\n",
              "stroke              0\n",
              "compressionratio    0\n",
              "horsepower          0\n",
              "peakrpm             0\n",
              "citympg             0\n",
              "highwaympg          0\n",
              "price               0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 86
        }
      ],
      "source": [
        "car_price.isnull().sum()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Checking the First Five Values in the Data**"
      ],
      "metadata": {
        "id": "0N934_m8w2aH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "car_price.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "id": "n5W6sMptHUxF",
        "outputId": "a0034e67-6f3f-40b9-da07-c6025ae3399a"
      },
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   car_ID  symboling                   CarName fueltype aspiration doornumber  \\\n",
              "0       1          3        alfa-romero giulia      gas        std        two   \n",
              "1       2          3       alfa-romero stelvio      gas        std        two   \n",
              "2       3          1  alfa-romero Quadrifoglio      gas        std        two   \n",
              "3       4          2               audi 100 ls      gas        std       four   \n",
              "4       5          2                audi 100ls      gas        std       four   \n",
              "\n",
              "       carbody drivewheel enginelocation  wheelbase  ...  enginesize  \\\n",
              "0  convertible        rwd          front       88.6  ...         130   \n",
              "1  convertible        rwd          front       88.6  ...         130   \n",
              "2    hatchback        rwd          front       94.5  ...         152   \n",
              "3        sedan        fwd          front       99.8  ...         109   \n",
              "4        sedan        4wd          front       99.4  ...         136   \n",
              "\n",
              "   fuelsystem  boreratio  stroke compressionratio horsepower  peakrpm citympg  \\\n",
              "0        mpfi       3.47    2.68              9.0        111     5000      21   \n",
              "1        mpfi       3.47    2.68              9.0        111     5000      21   \n",
              "2        mpfi       2.68    3.47              9.0        154     5000      19   \n",
              "3        mpfi       3.19    3.40             10.0        102     5500      24   \n",
              "4        mpfi       3.19    3.40              8.0        115     5500      18   \n",
              "\n",
              "   highwaympg    price  \n",
              "0          27  13495.0  \n",
              "1          27  16500.0  \n",
              "2          26  16500.0  \n",
              "3          30  13950.0  \n",
              "4          22  17450.0  \n",
              "\n",
              "[5 rows x 26 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a8a26c57-a272-45b9-8c5d-c75d2f88f353\">\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>car_ID</th>\n",
              "      <th>symboling</th>\n",
              "      <th>CarName</th>\n",
              "      <th>fueltype</th>\n",
              "      <th>aspiration</th>\n",
              "      <th>doornumber</th>\n",
              "      <th>carbody</th>\n",
              "      <th>drivewheel</th>\n",
              "      <th>enginelocation</th>\n",
              "      <th>wheelbase</th>\n",
              "      <th>...</th>\n",
              "      <th>enginesize</th>\n",
              "      <th>fuelsystem</th>\n",
              "      <th>boreratio</th>\n",
              "      <th>stroke</th>\n",
              "      <th>compressionratio</th>\n",
              "      <th>horsepower</th>\n",
              "      <th>peakrpm</th>\n",
              "      <th>citympg</th>\n",
              "      <th>highwaympg</th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>alfa-romero giulia</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>two</td>\n",
              "      <td>convertible</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>88.6</td>\n",
              "      <td>...</td>\n",
              "      <td>130</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>3.47</td>\n",
              "      <td>2.68</td>\n",
              "      <td>9.0</td>\n",
              "      <td>111</td>\n",
              "      <td>5000</td>\n",
              "      <td>21</td>\n",
              "      <td>27</td>\n",
              "      <td>13495.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>alfa-romero stelvio</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>two</td>\n",
              "      <td>convertible</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>88.6</td>\n",
              "      <td>...</td>\n",
              "      <td>130</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>3.47</td>\n",
              "      <td>2.68</td>\n",
              "      <td>9.0</td>\n",
              "      <td>111</td>\n",
              "      <td>5000</td>\n",
              "      <td>21</td>\n",
              "      <td>27</td>\n",
              "      <td>16500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>alfa-romero Quadrifoglio</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>two</td>\n",
              "      <td>hatchback</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>94.5</td>\n",
              "      <td>...</td>\n",
              "      <td>152</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>2.68</td>\n",
              "      <td>3.47</td>\n",
              "      <td>9.0</td>\n",
              "      <td>154</td>\n",
              "      <td>5000</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>16500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>audi 100 ls</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>fwd</td>\n",
              "      <td>front</td>\n",
              "      <td>99.8</td>\n",
              "      <td>...</td>\n",
              "      <td>109</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3.40</td>\n",
              "      <td>10.0</td>\n",
              "      <td>102</td>\n",
              "      <td>5500</td>\n",
              "      <td>24</td>\n",
              "      <td>30</td>\n",
              "      <td>13950.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>audi 100ls</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>4wd</td>\n",
              "      <td>front</td>\n",
              "      <td>99.4</td>\n",
              "      <td>...</td>\n",
              "      <td>136</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3.40</td>\n",
              "      <td>8.0</td>\n",
              "      <td>115</td>\n",
              "      <td>5500</td>\n",
              "      <td>18</td>\n",
              "      <td>22</td>\n",
              "      <td>17450.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 26 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a8a26c57-a272-45b9-8c5d-c75d2f88f353')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a8a26c57-a272-45b9-8c5d-c75d2f88f353 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-a8a26c57-a272-45b9-8c5d-c75d2f88f353');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Checking the Last Five Values in the Data**"
      ],
      "metadata": {
        "id": "11wXmVfVxERV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "car_price.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 404
        },
        "id": "RxX-_IbYHd2P",
        "outputId": "1a4e699c-f358-4b7d-d2c9-8c625bd2bdf9"
      },
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     car_ID  symboling          CarName fueltype aspiration doornumber  \\\n",
              "200     201         -1  volvo 145e (sw)      gas        std       four   \n",
              "201     202         -1      volvo 144ea      gas      turbo       four   \n",
              "202     203         -1      volvo 244dl      gas        std       four   \n",
              "203     204         -1        volvo 246   diesel      turbo       four   \n",
              "204     205         -1      volvo 264gl      gas      turbo       four   \n",
              "\n",
              "    carbody drivewheel enginelocation  wheelbase  ...  enginesize  fuelsystem  \\\n",
              "200   sedan        rwd          front      109.1  ...         141        mpfi   \n",
              "201   sedan        rwd          front      109.1  ...         141        mpfi   \n",
              "202   sedan        rwd          front      109.1  ...         173        mpfi   \n",
              "203   sedan        rwd          front      109.1  ...         145         idi   \n",
              "204   sedan        rwd          front      109.1  ...         141        mpfi   \n",
              "\n",
              "     boreratio  stroke compressionratio horsepower  peakrpm citympg  \\\n",
              "200       3.78    3.15              9.5        114     5400      23   \n",
              "201       3.78    3.15              8.7        160     5300      19   \n",
              "202       3.58    2.87              8.8        134     5500      18   \n",
              "203       3.01    3.40             23.0        106     4800      26   \n",
              "204       3.78    3.15              9.5        114     5400      19   \n",
              "\n",
              "     highwaympg    price  \n",
              "200          28  16845.0  \n",
              "201          25  19045.0  \n",
              "202          23  21485.0  \n",
              "203          27  22470.0  \n",
              "204          25  22625.0  \n",
              "\n",
              "[5 rows x 26 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-399b6783-7f9a-4340-9846-db9ef7aa13b1\">\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>car_ID</th>\n",
              "      <th>symboling</th>\n",
              "      <th>CarName</th>\n",
              "      <th>fueltype</th>\n",
              "      <th>aspiration</th>\n",
              "      <th>doornumber</th>\n",
              "      <th>carbody</th>\n",
              "      <th>drivewheel</th>\n",
              "      <th>enginelocation</th>\n",
              "      <th>wheelbase</th>\n",
              "      <th>...</th>\n",
              "      <th>enginesize</th>\n",
              "      <th>fuelsystem</th>\n",
              "      <th>boreratio</th>\n",
              "      <th>stroke</th>\n",
              "      <th>compressionratio</th>\n",
              "      <th>horsepower</th>\n",
              "      <th>peakrpm</th>\n",
              "      <th>citympg</th>\n",
              "      <th>highwaympg</th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>201</td>\n",
              "      <td>-1</td>\n",
              "      <td>volvo 145e (sw)</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>109.1</td>\n",
              "      <td>...</td>\n",
              "      <td>141</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>3.78</td>\n",
              "      <td>3.15</td>\n",
              "      <td>9.5</td>\n",
              "      <td>114</td>\n",
              "      <td>5400</td>\n",
              "      <td>23</td>\n",
              "      <td>28</td>\n",
              "      <td>16845.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>202</td>\n",
              "      <td>-1</td>\n",
              "      <td>volvo 144ea</td>\n",
              "      <td>gas</td>\n",
              "      <td>turbo</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>109.1</td>\n",
              "      <td>...</td>\n",
              "      <td>141</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>3.78</td>\n",
              "      <td>3.15</td>\n",
              "      <td>8.7</td>\n",
              "      <td>160</td>\n",
              "      <td>5300</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>19045.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>203</td>\n",
              "      <td>-1</td>\n",
              "      <td>volvo 244dl</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>109.1</td>\n",
              "      <td>...</td>\n",
              "      <td>173</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>3.58</td>\n",
              "      <td>2.87</td>\n",
              "      <td>8.8</td>\n",
              "      <td>134</td>\n",
              "      <td>5500</td>\n",
              "      <td>18</td>\n",
              "      <td>23</td>\n",
              "      <td>21485.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>204</td>\n",
              "      <td>-1</td>\n",
              "      <td>volvo 246</td>\n",
              "      <td>diesel</td>\n",
              "      <td>turbo</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>109.1</td>\n",
              "      <td>...</td>\n",
              "      <td>145</td>\n",
              "      <td>idi</td>\n",
              "      <td>3.01</td>\n",
              "      <td>3.40</td>\n",
              "      <td>23.0</td>\n",
              "      <td>106</td>\n",
              "      <td>4800</td>\n",
              "      <td>26</td>\n",
              "      <td>27</td>\n",
              "      <td>22470.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>205</td>\n",
              "      <td>-1</td>\n",
              "      <td>volvo 264gl</td>\n",
              "      <td>gas</td>\n",
              "      <td>turbo</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>109.1</td>\n",
              "      <td>...</td>\n",
              "      <td>141</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>3.78</td>\n",
              "      <td>3.15</td>\n",
              "      <td>9.5</td>\n",
              "      <td>114</td>\n",
              "      <td>5400</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>22625.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 26 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-399b6783-7f9a-4340-9846-db9ef7aa13b1')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-399b6783-7f9a-4340-9846-db9ef7aa13b1 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-399b6783-7f9a-4340-9846-db9ef7aa13b1');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Dimensions of the Dataset**"
      ],
      "metadata": {
        "id": "IjcRFzNmxsOO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "car_price.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bbLzaMuBHxaE",
        "outputId": "8a9f5308-8a4f-42c4-f439-2e4b5ba48e26"
      },
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(205, 26)"
            ]
          },
          "metadata": {},
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Describing the Dataset**"
      ],
      "metadata": {
        "id": "mNz5BHmRx5Zi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "car_price.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        },
        "id": "9HXdyo0wH2KH",
        "outputId": "b15446f8-fa92-4761-8950-bc4a6087e970"
      },
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           car_ID   symboling   wheelbase   carlength    carwidth   carheight  \\\n",
              "count  205.000000  205.000000  205.000000  205.000000  205.000000  205.000000   \n",
              "mean   103.000000    0.834146   98.756585  174.049268   65.907805   53.724878   \n",
              "std     59.322565    1.245307    6.021776   12.337289    2.145204    2.443522   \n",
              "min      1.000000   -2.000000   86.600000  141.100000   60.300000   47.800000   \n",
              "25%     52.000000    0.000000   94.500000  166.300000   64.100000   52.000000   \n",
              "50%    103.000000    1.000000   97.000000  173.200000   65.500000   54.100000   \n",
              "75%    154.000000    2.000000  102.400000  183.100000   66.900000   55.500000   \n",
              "max    205.000000    3.000000  120.900000  208.100000   72.300000   59.800000   \n",
              "\n",
              "        curbweight  enginesize   boreratio      stroke  compressionratio  \\\n",
              "count   205.000000  205.000000  205.000000  205.000000        205.000000   \n",
              "mean   2555.565854  126.907317    3.329756    3.255415         10.142537   \n",
              "std     520.680204   41.642693    0.270844    0.313597          3.972040   \n",
              "min    1488.000000   61.000000    2.540000    2.070000          7.000000   \n",
              "25%    2145.000000   97.000000    3.150000    3.110000          8.600000   \n",
              "50%    2414.000000  120.000000    3.310000    3.290000          9.000000   \n",
              "75%    2935.000000  141.000000    3.580000    3.410000          9.400000   \n",
              "max    4066.000000  326.000000    3.940000    4.170000         23.000000   \n",
              "\n",
              "       horsepower      peakrpm     citympg  highwaympg         price  \n",
              "count  205.000000   205.000000  205.000000  205.000000    205.000000  \n",
              "mean   104.117073  5125.121951   25.219512   30.751220  13276.710571  \n",
              "std     39.544167   476.985643    6.542142    6.886443   7988.852332  \n",
              "min     48.000000  4150.000000   13.000000   16.000000   5118.000000  \n",
              "25%     70.000000  4800.000000   19.000000   25.000000   7788.000000  \n",
              "50%     95.000000  5200.000000   24.000000   30.000000  10295.000000  \n",
              "75%    116.000000  5500.000000   30.000000   34.000000  16503.000000  \n",
              "max    288.000000  6600.000000   49.000000   54.000000  45400.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5ed84e4b-9e0a-420b-b57c-2fc351f00e7a\">\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>car_ID</th>\n",
              "      <th>symboling</th>\n",
              "      <th>wheelbase</th>\n",
              "      <th>carlength</th>\n",
              "      <th>carwidth</th>\n",
              "      <th>carheight</th>\n",
              "      <th>curbweight</th>\n",
              "      <th>enginesize</th>\n",
              "      <th>boreratio</th>\n",
              "      <th>stroke</th>\n",
              "      <th>compressionratio</th>\n",
              "      <th>horsepower</th>\n",
              "      <th>peakrpm</th>\n",
              "      <th>citympg</th>\n",
              "      <th>highwaympg</th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>205.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>103.000000</td>\n",
              "      <td>0.834146</td>\n",
              "      <td>98.756585</td>\n",
              "      <td>174.049268</td>\n",
              "      <td>65.907805</td>\n",
              "      <td>53.724878</td>\n",
              "      <td>2555.565854</td>\n",
              "      <td>126.907317</td>\n",
              "      <td>3.329756</td>\n",
              "      <td>3.255415</td>\n",
              "      <td>10.142537</td>\n",
              "      <td>104.117073</td>\n",
              "      <td>5125.121951</td>\n",
              "      <td>25.219512</td>\n",
              "      <td>30.751220</td>\n",
              "      <td>13276.710571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>59.322565</td>\n",
              "      <td>1.245307</td>\n",
              "      <td>6.021776</td>\n",
              "      <td>12.337289</td>\n",
              "      <td>2.145204</td>\n",
              "      <td>2.443522</td>\n",
              "      <td>520.680204</td>\n",
              "      <td>41.642693</td>\n",
              "      <td>0.270844</td>\n",
              "      <td>0.313597</td>\n",
              "      <td>3.972040</td>\n",
              "      <td>39.544167</td>\n",
              "      <td>476.985643</td>\n",
              "      <td>6.542142</td>\n",
              "      <td>6.886443</td>\n",
              "      <td>7988.852332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-2.000000</td>\n",
              "      <td>86.600000</td>\n",
              "      <td>141.100000</td>\n",
              "      <td>60.300000</td>\n",
              "      <td>47.800000</td>\n",
              "      <td>1488.000000</td>\n",
              "      <td>61.000000</td>\n",
              "      <td>2.540000</td>\n",
              "      <td>2.070000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>48.000000</td>\n",
              "      <td>4150.000000</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>5118.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>52.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>94.500000</td>\n",
              "      <td>166.300000</td>\n",
              "      <td>64.100000</td>\n",
              "      <td>52.000000</td>\n",
              "      <td>2145.000000</td>\n",
              "      <td>97.000000</td>\n",
              "      <td>3.150000</td>\n",
              "      <td>3.110000</td>\n",
              "      <td>8.600000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>4800.000000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>7788.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>103.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>97.000000</td>\n",
              "      <td>173.200000</td>\n",
              "      <td>65.500000</td>\n",
              "      <td>54.100000</td>\n",
              "      <td>2414.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>3.310000</td>\n",
              "      <td>3.290000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>95.000000</td>\n",
              "      <td>5200.000000</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>10295.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>154.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>102.400000</td>\n",
              "      <td>183.100000</td>\n",
              "      <td>66.900000</td>\n",
              "      <td>55.500000</td>\n",
              "      <td>2935.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>3.580000</td>\n",
              "      <td>3.410000</td>\n",
              "      <td>9.400000</td>\n",
              "      <td>116.000000</td>\n",
              "      <td>5500.000000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>34.000000</td>\n",
              "      <td>16503.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>205.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>120.900000</td>\n",
              "      <td>208.100000</td>\n",
              "      <td>72.300000</td>\n",
              "      <td>59.800000</td>\n",
              "      <td>4066.000000</td>\n",
              "      <td>326.000000</td>\n",
              "      <td>3.940000</td>\n",
              "      <td>4.170000</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>288.000000</td>\n",
              "      <td>6600.000000</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>54.000000</td>\n",
              "      <td>45400.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5ed84e4b-9e0a-420b-b57c-2fc351f00e7a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5ed84e4b-9e0a-420b-b57c-2fc351f00e7a 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-5ed84e4b-9e0a-420b-b57c-2fc351f00e7a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Checking for the classes in the Data**"
      ],
      "metadata": {
        "id": "csEfkNNvyECS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "car_price.groupby('carbody').size()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AOrsLgfeI0Gv",
        "outputId": "18efaf97-a7c6-4ce1-bfe9-77b243570a03"
      },
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "carbody\n",
              "convertible     6\n",
              "hardtop         8\n",
              "hatchback      70\n",
              "sedan          96\n",
              "wagon          25\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Taking the required Informations**"
      ],
      "metadata": {
        "id": "WkeOgzCjJvmR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "car = car_price[[\"symboling\", \"wheelbase\", \"carlength\", \"carwidth\", \"carheight\", \"curbweight\", \"enginesize\", \"boreratio\", \"stroke\", \"compressionratio\", \"horsepower\", \"peakrpm\", \"citympg\", \"highwaympg\", \"price\"]]\n",
        "car"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "fMhP6E_KJS4p",
        "outputId": "cda5e502-38e3-4cbd-be67-fbb884943a66"
      },
      "execution_count": 92,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     symboling  wheelbase  carlength  carwidth  carheight  curbweight  \\\n",
              "0            3       88.6      168.8      64.1       48.8        2548   \n",
              "1            3       88.6      168.8      64.1       48.8        2548   \n",
              "2            1       94.5      171.2      65.5       52.4        2823   \n",
              "3            2       99.8      176.6      66.2       54.3        2337   \n",
              "4            2       99.4      176.6      66.4       54.3        2824   \n",
              "..         ...        ...        ...       ...        ...         ...   \n",
              "200         -1      109.1      188.8      68.9       55.5        2952   \n",
              "201         -1      109.1      188.8      68.8       55.5        3049   \n",
              "202         -1      109.1      188.8      68.9       55.5        3012   \n",
              "203         -1      109.1      188.8      68.9       55.5        3217   \n",
              "204         -1      109.1      188.8      68.9       55.5        3062   \n",
              "\n",
              "     enginesize  boreratio  stroke  compressionratio  horsepower  peakrpm  \\\n",
              "0           130       3.47    2.68               9.0         111     5000   \n",
              "1           130       3.47    2.68               9.0         111     5000   \n",
              "2           152       2.68    3.47               9.0         154     5000   \n",
              "3           109       3.19    3.40              10.0         102     5500   \n",
              "4           136       3.19    3.40               8.0         115     5500   \n",
              "..          ...        ...     ...               ...         ...      ...   \n",
              "200         141       3.78    3.15               9.5         114     5400   \n",
              "201         141       3.78    3.15               8.7         160     5300   \n",
              "202         173       3.58    2.87               8.8         134     5500   \n",
              "203         145       3.01    3.40              23.0         106     4800   \n",
              "204         141       3.78    3.15               9.5         114     5400   \n",
              "\n",
              "     citympg  highwaympg    price  \n",
              "0         21          27  13495.0  \n",
              "1         21          27  16500.0  \n",
              "2         19          26  16500.0  \n",
              "3         24          30  13950.0  \n",
              "4         18          22  17450.0  \n",
              "..       ...         ...      ...  \n",
              "200       23          28  16845.0  \n",
              "201       19          25  19045.0  \n",
              "202       18          23  21485.0  \n",
              "203       26          27  22470.0  \n",
              "204       19          25  22625.0  \n",
              "\n",
              "[205 rows x 15 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ffce1a31-2258-4e89-ab70-1ad610f4620b\">\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>symboling</th>\n",
              "      <th>wheelbase</th>\n",
              "      <th>carlength</th>\n",
              "      <th>carwidth</th>\n",
              "      <th>carheight</th>\n",
              "      <th>curbweight</th>\n",
              "      <th>enginesize</th>\n",
              "      <th>boreratio</th>\n",
              "      <th>stroke</th>\n",
              "      <th>compressionratio</th>\n",
              "      <th>horsepower</th>\n",
              "      <th>peakrpm</th>\n",
              "      <th>citympg</th>\n",
              "      <th>highwaympg</th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3</td>\n",
              "      <td>88.6</td>\n",
              "      <td>168.8</td>\n",
              "      <td>64.1</td>\n",
              "      <td>48.8</td>\n",
              "      <td>2548</td>\n",
              "      <td>130</td>\n",
              "      <td>3.47</td>\n",
              "      <td>2.68</td>\n",
              "      <td>9.0</td>\n",
              "      <td>111</td>\n",
              "      <td>5000</td>\n",
              "      <td>21</td>\n",
              "      <td>27</td>\n",
              "      <td>13495.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>88.6</td>\n",
              "      <td>168.8</td>\n",
              "      <td>64.1</td>\n",
              "      <td>48.8</td>\n",
              "      <td>2548</td>\n",
              "      <td>130</td>\n",
              "      <td>3.47</td>\n",
              "      <td>2.68</td>\n",
              "      <td>9.0</td>\n",
              "      <td>111</td>\n",
              "      <td>5000</td>\n",
              "      <td>21</td>\n",
              "      <td>27</td>\n",
              "      <td>16500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>94.5</td>\n",
              "      <td>171.2</td>\n",
              "      <td>65.5</td>\n",
              "      <td>52.4</td>\n",
              "      <td>2823</td>\n",
              "      <td>152</td>\n",
              "      <td>2.68</td>\n",
              "      <td>3.47</td>\n",
              "      <td>9.0</td>\n",
              "      <td>154</td>\n",
              "      <td>5000</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>16500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>99.8</td>\n",
              "      <td>176.6</td>\n",
              "      <td>66.2</td>\n",
              "      <td>54.3</td>\n",
              "      <td>2337</td>\n",
              "      <td>109</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3.40</td>\n",
              "      <td>10.0</td>\n",
              "      <td>102</td>\n",
              "      <td>5500</td>\n",
              "      <td>24</td>\n",
              "      <td>30</td>\n",
              "      <td>13950.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>99.4</td>\n",
              "      <td>176.6</td>\n",
              "      <td>66.4</td>\n",
              "      <td>54.3</td>\n",
              "      <td>2824</td>\n",
              "      <td>136</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3.40</td>\n",
              "      <td>8.0</td>\n",
              "      <td>115</td>\n",
              "      <td>5500</td>\n",
              "      <td>18</td>\n",
              "      <td>22</td>\n",
              "      <td>17450.0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>-1</td>\n",
              "      <td>109.1</td>\n",
              "      <td>188.8</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>2952</td>\n",
              "      <td>141</td>\n",
              "      <td>3.78</td>\n",
              "      <td>3.15</td>\n",
              "      <td>9.5</td>\n",
              "      <td>114</td>\n",
              "      <td>5400</td>\n",
              "      <td>23</td>\n",
              "      <td>28</td>\n",
              "      <td>16845.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>-1</td>\n",
              "      <td>109.1</td>\n",
              "      <td>188.8</td>\n",
              "      <td>68.8</td>\n",
              "      <td>55.5</td>\n",
              "      <td>3049</td>\n",
              "      <td>141</td>\n",
              "      <td>3.78</td>\n",
              "      <td>3.15</td>\n",
              "      <td>8.7</td>\n",
              "      <td>160</td>\n",
              "      <td>5300</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>19045.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>-1</td>\n",
              "      <td>109.1</td>\n",
              "      <td>188.8</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>3012</td>\n",
              "      <td>173</td>\n",
              "      <td>3.58</td>\n",
              "      <td>2.87</td>\n",
              "      <td>8.8</td>\n",
              "      <td>134</td>\n",
              "      <td>5500</td>\n",
              "      <td>18</td>\n",
              "      <td>23</td>\n",
              "      <td>21485.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>-1</td>\n",
              "      <td>109.1</td>\n",
              "      <td>188.8</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>3217</td>\n",
              "      <td>145</td>\n",
              "      <td>3.01</td>\n",
              "      <td>3.40</td>\n",
              "      <td>23.0</td>\n",
              "      <td>106</td>\n",
              "      <td>4800</td>\n",
              "      <td>26</td>\n",
              "      <td>27</td>\n",
              "      <td>22470.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>-1</td>\n",
              "      <td>109.1</td>\n",
              "      <td>188.8</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>3062</td>\n",
              "      <td>141</td>\n",
              "      <td>3.78</td>\n",
              "      <td>3.15</td>\n",
              "      <td>9.5</td>\n",
              "      <td>114</td>\n",
              "      <td>5400</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>22625.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>205 rows × 15 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ffce1a31-2258-4e89-ab70-1ad610f4620b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ffce1a31-2258-4e89-ab70-1ad610f4620b 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-ffce1a31-2258-4e89-ab70-1ad610f4620b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Plotting the Bivariate Bar for the Dataset**"
      ],
      "metadata": {
        "id": "JH4lQS9vKo_E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_bivariate_bar(dataset, cols, width, height, hspace, wspace):\n",
        "    dataset = dataset.select_dtypes(include = [np.int64])\n",
        "    plt.style.use('seaborn-whitegrid')\n",
        "    fig = plt.figure(figsize=(width, height))\n",
        "    fig.subplots_adjust(left = None, bottom = None, right = None, top = None, wspace = wspace, hspace = hspace)\n",
        "    rows = math.ceil(float(dataset.shape[1]) / cols)\n",
        "    for i, column in enumerate(dataset.columns):\n",
        "        ax = fig.add_subplot(rows, cols, i + 1)\n",
        "        ax.set_title(column)\n",
        "        if dataset.dtypes[column] == np.int64:\n",
        "            g = sns.countplot(y = column, data = dataset)\n",
        "            substrings = [s.get_text()[:15] for s in g.get_yticklabels()]\n",
        "            g.set(yticklabels = substrings)\n",
        "\n",
        "plot_bivariate_bar(car, cols = 5, width = 20, height = 15, hspace = 0.2, wspace = 0.5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 944
        },
        "id": "C_GtjoiUJ2Vk",
        "outputId": "07b32fd0-c14a-49db-d79d-d82063b3956e"
      },
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-93-633c2a59e43d>:3: MatplotlibDeprecationWarning: The seaborn styles shipped by Matplotlib are deprecated since 3.6, as they no longer correspond to the styles shipped by seaborn. However, they will remain available as 'seaborn-v0_8-<style>'. Alternatively, directly use the seaborn API instead.\n",
            "  plt.style.use('seaborn-whitegrid')\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x1080 with 7 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Plotting the Joint Plot for the Dataset**"
      ],
      "metadata": {
        "id": "HKGW3U_aK3Xu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (10, 10))\n",
        "sns.jointplot(data = car)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "9TELvDXjKjfH",
        "outputId": "7daeab87-6b6f-476c-ef40-6b0d37501988"
      },
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 3 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Plotting the Correlation Matrix of the Dataset**"
      ],
      "metadata": {
        "id": "OfNbgZZ0LHbC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (20, 10))\n",
        "sns.set_style('darkgrid')\n",
        "sns.heatmap(car.corr(), annot = True, cmap = 'viridis')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 668
        },
        "id": "3SLIAZQ2LB9K",
        "outputId": "85c9f85f-9ba5-4ded-a86f-4b5d045b2a04"
      },
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x = car.drop([\"price\"], 1)\n",
        "y = car[\"price\"]\n",
        "xtrain, xtest, ytrain, ytest = train_test_split(x, y, random_state = 16, test_size = 0.25, shuffle=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xUqyeti_LXtz",
        "outputId": "4d391135-d9fd-44d3-b7fb-ba23d30f7724"
      },
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-96-097e32681f69>:1: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only.\n",
            "  x = car.drop([\"price\"], 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Model Building"
      ],
      "metadata": {
        "id": "hgGiShUfMers"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Creating the Model**"
      ],
      "metadata": {
        "id": "6JJXCiMiM4yW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model1 = LinearRegression()\n",
        "model2 = DecisionTreeRegressor()"
      ],
      "metadata": {
        "id": "lxlL1rqvL5kf"
      },
      "execution_count": 97,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Fitting the Model**"
      ],
      "metadata": {
        "id": "8sCLVY5FOCYL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model1.fit(xtrain, ytrain)\n",
        "model1.score(xtrain, ytrain)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZkuNgn3KM-2j",
        "outputId": "fb5fad75-1f48-49f1-db33-5f9cdc10ae33"
      },
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8330089871124585"
            ]
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model2.fit(xtrain, ytrain)\n",
        "model2.score(xtrain, ytrain)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HqUYgkvyOKlf",
        "outputId": "8bcc3615-8eb3-4a65-a165-2344f5703759"
      },
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9997917694852244"
            ]
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Testing Model"
      ],
      "metadata": {
        "id": "mU7WPfABOTrs"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Testing the Model**"
      ],
      "metadata": {
        "id": "LuRXD6ZBOcOb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "Linear_predictions = model1.predict(xtest)\n",
        "Decision_predictions = model2.predict(xtest)"
      ],
      "metadata": {
        "id": "oaGtFa2kOsgZ"
      },
      "execution_count": 100,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Metrics**"
      ],
      "metadata": {
        "id": "YtV3kz1OPYZz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Linear Regression Model:\")\n",
        "print(\"************************\")\n",
        "print('R2_score:', r2_score(ytest, Linear_predictions))\n",
        "print('Mean Absolute Error:', mean_absolute_error(ytest, Linear_predictions))\n",
        "print('Mean Squared Error:', mean_squared_error(ytest, Linear_predictions))\n",
        "print('Root Mean Squared Error:', np.sqrt(mean_squared_error(ytest, Linear_predictions)))\n",
        "print(\"---------------------------------------------\")\n",
        "print(\"Decision Tree Regression Model:\")\n",
        "print(\"******************************\")\n",
        "print('R2_score:', r2_score(ytest, Decision_predictions))\n",
        "print('Mean Absolute Error:', mean_absolute_error(ytest, Decision_predictions))\n",
        "print('Mean Squared Error:', mean_squared_error(ytest, Decision_predictions))\n",
        "print('Root Mean Squared Error:', np.sqrt(mean_squared_error(ytest, Decision_predictions)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XGKW3rLXO07q",
        "outputId": "48194c72-6717-4db8-d24d-2123553f149b"
      },
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Linear Regression Model:\n",
            "************************\n",
            "R2_score: 0.8862171911494976\n",
            "Mean Absolute Error: 2145.7908919291503\n",
            "Mean Squared Error: 7974570.967268005\n",
            "Root Mean Squared Error: 2823.928286495251\n",
            "---------------------------------------------\n",
            "Decision Tree Regression Model:\n",
            "******************************\n",
            "R2_score: 0.9469373524561051\n",
            "Mean Absolute Error: 1342.1185961538463\n",
            "Mean Squared Error: 3718943.5981132505\n",
            "Root Mean Squared Error: 1928.4562733215525\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Accuracy of Linear Regression Model: \", model1.score(xtrain, ytrain))\n",
        "print(\"Accuracy of Decision Tree Regression Model: \", model2.score(xtrain, ytrain))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mo_7-iCrFmvq",
        "outputId": "a107adf8-835b-4e2f-ba05-fde1c570d7d1"
      },
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of Linear Regression Model:  0.8330089871124585\n",
            "Accuracy of Decision Tree Regression Model:  0.9997917694852244\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Saving Models"
      ],
      "metadata": {
        "id": "SPCOZEI1QgBU"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Saving the Models**"
      ],
      "metadata": {
        "id": "N4GX2woxQncg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "filename = \"Linear_Regression.pkl\"\n",
        "pickle.dump(model1, open(filename, 'wb'))\n",
        "filename = \"Decision_Tree_Regressor.pkl\"\n",
        "pickle.dump(model2, open(filename, 'wb'))\n",
        "print(\"Saved all Models\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "liNVD7WPQnAg",
        "outputId": "a47ccd74-2fb6-49ae-b1a7-4182266d4c4d"
      },
      "execution_count": 103,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saved all Models\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}