Car_Price_Prediction_assignment (5).ipynb

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    "colab": {
      "name": "Car_Price_Prediction_assignment.ipynb",
      "provenance": [],
      "collapsed_sections": []
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0_HsWVrWvDNP"
      },
      "source": [
        "# Car Price Prediction::"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Neq61yUOvDNV"
      },
      "source": [
        "Download dataset from this link:\n",
        "\n",
        "https://www.kaggle.com/hellbuoy/car-price-prediction"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "errs9eyZvDNW"
      },
      "source": [
        "# Problem Statement::"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "92PLZp2kwKxv",
        "outputId": "beb4af94-0973-418a-f982-4a446d6419ee"
      },
      "source": [
        "# mount google drive in to your Colab enviornment\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yvDEDSF3yS1S",
        "outputId": "351ddd9d-eea3-4b4b-c44a-414410fcb1af"
      },
      "source": [
        "cd /content/drive/MyDrive/AI_assignment/\n"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/drive/MyDrive/AI_assignment\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zCu6NRLVvDNX"
      },
      "source": [
        "A Chinese automobile company Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts.\n",
        "\n",
        "They have contracted an automobile consulting company to understand the factors on which the pricing of cars depends. Specifically, they want to understand the factors affecting the pricing of cars in the American market, since those may be very different from the Chinese market. The company wants to know:\n",
        "\n",
        "Which variables are significant in predicting the price of a car\n",
        "How well those variables describe the price of a car\n",
        "Based on various market surveys, the consulting firm has gathered a large data set of different types of cars across the America market.\n",
        "\n",
        "# task::\n",
        "We are required to model the price of cars with the available independent variables. It will be used by the management to understand how exactly the prices vary with the independent variables. They can accordingly manipulate the design of the cars, the business strategy etc. to meet certain price levels. Further, the model will be a good way for management to understand the pricing dynamics of a new market."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3-vI6CymvDNX"
      },
      "source": [
        "# WORKFLOW ::"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mRvlK8RBvDNX"
      },
      "source": [
        "1.Load Data\n",
        "\n",
        "2.Check Missing Values ( If Exist ; Fill each record with mean of its feature )\n",
        "\n",
        "3.Split into 50% Training(Samples,Labels) , 30% Test(Samples,Labels) and 20% Validation Data(Samples,Labels).\n",
        "\n",
        "4.Model : input Layer (No. of features ), 3 hidden layers including 10,8,6 unit & Output Layer with activation function relu/tanh (check by experiment).\n",
        "\n",
        "5.Compilation Step (Note : Its a Regression problem , select loss , metrics according to it)\n",
        "6.Train the Model with Epochs (100) and validate it\n",
        "\n",
        "7.If the model gets overfit tune your model by changing the units , No. of layers , activation function , epochs , add dropout layer or add Regularizer according to the need .\n",
        "\n",
        "8.Evaluation Step\n",
        "\n",
        "9.Prediction"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "duXMXXhZvDNY"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "car_data = pd.read_csv('./CarPrice_Assignment.csv')"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vd2sfUEUPRvi"
      },
      "source": [
        "import tensorflow as tf"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "id": "-JRgNW0hzOVH",
        "outputId": "217aad59-e229-424e-a03d-1021862bec64"
      },
      "source": [
        "car_data"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</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>carlength</th>\n",
              "      <th>carwidth</th>\n",
              "      <th>carheight</th>\n",
              "      <th>curbweight</th>\n",
              "      <th>enginetype</th>\n",
              "      <th>cylindernumber</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>168.8</td>\n",
              "      <td>64.1</td>\n",
              "      <td>48.8</td>\n",
              "      <td>2548</td>\n",
              "      <td>dohc</td>\n",
              "      <td>four</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>168.8</td>\n",
              "      <td>64.1</td>\n",
              "      <td>48.8</td>\n",
              "      <td>2548</td>\n",
              "      <td>dohc</td>\n",
              "      <td>four</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>171.2</td>\n",
              "      <td>65.5</td>\n",
              "      <td>52.4</td>\n",
              "      <td>2823</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>six</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>176.6</td>\n",
              "      <td>66.2</td>\n",
              "      <td>54.3</td>\n",
              "      <td>2337</td>\n",
              "      <td>ohc</td>\n",
              "      <td>four</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>176.6</td>\n",
              "      <td>66.4</td>\n",
              "      <td>54.3</td>\n",
              "      <td>2824</td>\n",
              "      <td>ohc</td>\n",
              "      <td>five</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",
              "    <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",
              "      <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>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>188.8</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>2952</td>\n",
              "      <td>ohc</td>\n",
              "      <td>four</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>188.8</td>\n",
              "      <td>68.8</td>\n",
              "      <td>55.5</td>\n",
              "      <td>3049</td>\n",
              "      <td>ohc</td>\n",
              "      <td>four</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>188.8</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>3012</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>six</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>188.8</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>3217</td>\n",
              "      <td>ohc</td>\n",
              "      <td>six</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>188.8</td>\n",
              "      <td>68.9</td>\n",
              "      <td>55.5</td>\n",
              "      <td>3062</td>\n",
              "      <td>ohc</td>\n",
              "      <td>four</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>205 rows × 26 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     car_ID  symboling                   CarName  ... citympg highwaympg    price\n",
              "0         1          3        alfa-romero giulia  ...      21         27  13495.0\n",
              "1         2          3       alfa-romero stelvio  ...      21         27  16500.0\n",
              "2         3          1  alfa-romero Quadrifoglio  ...      19         26  16500.0\n",
              "3         4          2               audi 100 ls  ...      24         30  13950.0\n",
              "4         5          2                audi 100ls  ...      18         22  17450.0\n",
              "..      ...        ...                       ...  ...     ...        ...      ...\n",
              "200     201         -1           volvo 145e (sw)  ...      23         28  16845.0\n",
              "201     202         -1               volvo 144ea  ...      19         25  19045.0\n",
              "202     203         -1               volvo 244dl  ...      18         23  21485.0\n",
              "203     204         -1                 volvo 246  ...      26         27  22470.0\n",
              "204     205         -1               volvo 264gl  ...      19         25  22625.0\n",
              "\n",
              "[205 rows x 26 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H6NTeH-qvDNa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "03ce84a4-904d-44ff-8262-8b580fceace6"
      },
      "source": [
        "#check if there are empty cells, if there are then row and column indexes will be returned where values are empty or missing\n",
        "np.where(car_data.applymap(lambda x: x ==''))"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([], dtype=int64), array([], dtype=int64))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "euCqFI3Y0l6h",
        "outputId": "4b631c08-2d4e-4071-dddf-8c0dcc847260"
      },
      "source": [
        "car_data.isnull().any()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "car_ID              False\n",
              "symboling           False\n",
              "CarName             False\n",
              "fueltype            False\n",
              "aspiration          False\n",
              "doornumber          False\n",
              "carbody             False\n",
              "drivewheel          False\n",
              "enginelocation      False\n",
              "wheelbase           False\n",
              "carlength           False\n",
              "carwidth            False\n",
              "carheight           False\n",
              "curbweight          False\n",
              "enginetype          False\n",
              "cylindernumber      False\n",
              "enginesize          False\n",
              "fuelsystem          False\n",
              "boreratio           False\n",
              "stroke              False\n",
              "compressionratio    False\n",
              "horsepower          False\n",
              "peakrpm             False\n",
              "citympg             False\n",
              "highwaympg          False\n",
              "price               False\n",
              "dtype: bool"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gBJA5-NyX-zj"
      },
      "source": [
        "# drop useless column\n",
        "car_data.drop(columns = ['car_ID','CarName'], inplace= True)"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D6itRa1UvR67"
      },
      "source": [
        "#check if there are ambigous names or wrong strings here you will see 'audi 100 ls' and 'audi 100ls' have same \n",
        "#name but a space between '100 ls' will create an extra feature, which is not desireable, we will correct this name in next cell\n",
        "# car_data['CarName'].unique()"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UwZgj7IIvXRm"
      },
      "source": [
        "# correct the name error in audi 100 ls\n",
        "# car_data.iloc[3,2] = 'audi 100ls'"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r1cCvWApvDNZ",
        "outputId": "65cbedbb-6840-494b-9640-8489cded58d0"
      },
      "source": [
        "car_data.dtypes"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "symboling             int64\n",
              "fueltype             object\n",
              "aspiration           object\n",
              "doornumber           object\n",
              "carbody              object\n",
              "drivewheel           object\n",
              "enginelocation       object\n",
              "wheelbase           float64\n",
              "carlength           float64\n",
              "carwidth            float64\n",
              "carheight           float64\n",
              "curbweight            int64\n",
              "enginetype           object\n",
              "cylindernumber       object\n",
              "enginesize            int64\n",
              "fuelsystem           object\n",
              "boreratio           float64\n",
              "stroke              float64\n",
              "compressionratio    float64\n",
              "horsepower            int64\n",
              "peakrpm               int64\n",
              "citympg               int64\n",
              "highwaympg            int64\n",
              "price               float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BN6vZOZr5EpP",
        "outputId": "9ffefc7b-c691-4268-83f2-263978bc1fcc"
      },
      "source": [
        "# get columns so that we can use the column names for onehot encoding of catagorical featrues in next cell\n",
        "car_data.columns"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['symboling', 'fueltype', 'aspiration', 'doornumber', 'carbody',\n",
              "       'drivewheel', 'enginelocation', 'wheelbase', 'carlength', 'carwidth',\n",
              "       'carheight', 'curbweight', 'enginetype', 'cylindernumber', 'enginesize',\n",
              "       'fuelsystem', 'boreratio', 'stroke', 'compressionratio', 'horsepower',\n",
              "       'peakrpm', 'citympg', 'highwaympg', 'price'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nqvKX-JyvDNa"
      },
      "source": [
        "# onehot encode all catagorical columns\n",
        "final_car = pd.get_dummies(car_data, columns=['symboling','fueltype',\t'aspiration',\t'doornumber',\t'carbody',\t'drivewheel',\t'enginelocation',\t'enginetype',\t'cylindernumber',\t'fuelsystem'])\n"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hgIZc8J6UswW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "outputId": "72c8681d-1772-4c1c-a9fa-ff543d754349"
      },
      "source": [
        "#check statistical data to see abnormal values and outliers\n",
        "final_car.describe()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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",
              "      <th>symboling_-2</th>\n",
              "      <th>symboling_-1</th>\n",
              "      <th>symboling_0</th>\n",
              "      <th>symboling_1</th>\n",
              "      <th>symboling_2</th>\n",
              "      <th>symboling_3</th>\n",
              "      <th>fueltype_diesel</th>\n",
              "      <th>fueltype_gas</th>\n",
              "      <th>aspiration_std</th>\n",
              "      <th>aspiration_turbo</th>\n",
              "      <th>doornumber_four</th>\n",
              "      <th>doornumber_two</th>\n",
              "      <th>carbody_convertible</th>\n",
              "      <th>carbody_hardtop</th>\n",
              "      <th>carbody_hatchback</th>\n",
              "      <th>carbody_sedan</th>\n",
              "      <th>carbody_wagon</th>\n",
              "      <th>drivewheel_4wd</th>\n",
              "      <th>drivewheel_fwd</th>\n",
              "      <th>drivewheel_rwd</th>\n",
              "      <th>enginelocation_front</th>\n",
              "      <th>enginelocation_rear</th>\n",
              "      <th>enginetype_dohc</th>\n",
              "      <th>enginetype_dohcv</th>\n",
              "      <th>enginetype_l</th>\n",
              "      <th>enginetype_ohc</th>\n",
              "      <th>enginetype_ohcf</th>\n",
              "      <th>enginetype_ohcv</th>\n",
              "      <th>enginetype_rotor</th>\n",
              "      <th>cylindernumber_eight</th>\n",
              "      <th>cylindernumber_five</th>\n",
              "      <th>cylindernumber_four</th>\n",
              "      <th>cylindernumber_six</th>\n",
              "      <th>cylindernumber_three</th>\n",
              "      <th>cylindernumber_twelve</th>\n",
              "      <th>cylindernumber_two</th>\n",
              "      <th>fuelsystem_1bbl</th>\n",
              "      <th>fuelsystem_2bbl</th>\n",
              "      <th>fuelsystem_4bbl</th>\n",
              "      <th>fuelsystem_idi</th>\n",
              "      <th>fuelsystem_mfi</th>\n",
              "      <th>fuelsystem_mpfi</th>\n",
              "      <th>fuelsystem_spdi</th>\n",
              "      <th>fuelsystem_spfi</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",
              "      <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",
              "      <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",
              "      <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>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",
              "      <td>0.014634</td>\n",
              "      <td>0.107317</td>\n",
              "      <td>0.326829</td>\n",
              "      <td>0.263415</td>\n",
              "      <td>0.156098</td>\n",
              "      <td>0.131707</td>\n",
              "      <td>0.097561</td>\n",
              "      <td>0.902439</td>\n",
              "      <td>0.819512</td>\n",
              "      <td>0.180488</td>\n",
              "      <td>0.560976</td>\n",
              "      <td>0.439024</td>\n",
              "      <td>0.029268</td>\n",
              "      <td>0.039024</td>\n",
              "      <td>0.341463</td>\n",
              "      <td>0.468293</td>\n",
              "      <td>0.121951</td>\n",
              "      <td>0.043902</td>\n",
              "      <td>0.585366</td>\n",
              "      <td>0.370732</td>\n",
              "      <td>0.985366</td>\n",
              "      <td>0.014634</td>\n",
              "      <td>0.058537</td>\n",
              "      <td>0.004878</td>\n",
              "      <td>0.058537</td>\n",
              "      <td>0.721951</td>\n",
              "      <td>0.073171</td>\n",
              "      <td>0.063415</td>\n",
              "      <td>0.019512</td>\n",
              "      <td>0.024390</td>\n",
              "      <td>0.053659</td>\n",
              "      <td>0.775610</td>\n",
              "      <td>0.117073</td>\n",
              "      <td>0.004878</td>\n",
              "      <td>0.004878</td>\n",
              "      <td>0.019512</td>\n",
              "      <td>0.053659</td>\n",
              "      <td>0.321951</td>\n",
              "      <td>0.014634</td>\n",
              "      <td>0.097561</td>\n",
              "      <td>0.004878</td>\n",
              "      <td>0.458537</td>\n",
              "      <td>0.043902</td>\n",
              "      <td>0.004878</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\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",
              "      <td>0.120377</td>\n",
              "      <td>0.310274</td>\n",
              "      <td>0.470202</td>\n",
              "      <td>0.441564</td>\n",
              "      <td>0.363836</td>\n",
              "      <td>0.339000</td>\n",
              "      <td>0.297446</td>\n",
              "      <td>0.297446</td>\n",
              "      <td>0.385535</td>\n",
              "      <td>0.385535</td>\n",
              "      <td>0.497483</td>\n",
              "      <td>0.497483</td>\n",
              "      <td>0.168970</td>\n",
              "      <td>0.194127</td>\n",
              "      <td>0.475361</td>\n",
              "      <td>0.500215</td>\n",
              "      <td>0.328031</td>\n",
              "      <td>0.205380</td>\n",
              "      <td>0.493865</td>\n",
              "      <td>0.484183</td>\n",
              "      <td>0.120377</td>\n",
              "      <td>0.120377</td>\n",
              "      <td>0.235330</td>\n",
              "      <td>0.069843</td>\n",
              "      <td>0.235330</td>\n",
              "      <td>0.449134</td>\n",
              "      <td>0.261054</td>\n",
              "      <td>0.244304</td>\n",
              "      <td>0.138655</td>\n",
              "      <td>0.154635</td>\n",
              "      <td>0.225894</td>\n",
              "      <td>0.418201</td>\n",
              "      <td>0.322294</td>\n",
              "      <td>0.069843</td>\n",
              "      <td>0.069843</td>\n",
              "      <td>0.138655</td>\n",
              "      <td>0.225894</td>\n",
              "      <td>0.468368</td>\n",
              "      <td>0.120377</td>\n",
              "      <td>0.297446</td>\n",
              "      <td>0.069843</td>\n",
              "      <td>0.499498</td>\n",
              "      <td>0.205380</td>\n",
              "      <td>0.069843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\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",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\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",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\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",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\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",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\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",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        wheelbase   carlength  ...  fuelsystem_spdi  fuelsystem_spfi\n",
              "count  205.000000  205.000000  ...       205.000000       205.000000\n",
              "mean    98.756585  174.049268  ...         0.043902         0.004878\n",
              "std      6.021776   12.337289  ...         0.205380         0.069843\n",
              "min     86.600000  141.100000  ...         0.000000         0.000000\n",
              "25%     94.500000  166.300000  ...         0.000000         0.000000\n",
              "50%     97.000000  173.200000  ...         0.000000         0.000000\n",
              "75%    102.400000  183.100000  ...         0.000000         0.000000\n",
              "max    120.900000  208.100000  ...         1.000000         1.000000\n",
              "\n",
              "[8 rows x 58 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q_sikuUQAGD4"
      },
      "source": [
        "#initialize a seed value so that each time we can get the same random number sequence, it will help us  as a team\n",
        "# working on a common project to work on the same random data. Each new seed will generate a particular sequnce\n",
        "#of random number. You can choose any seed value here of your choice\n",
        "# 0.72 means we have taken 72% values for training set as we will make 72/4 = 18 rows of k fold validation data, where\n",
        "# value of k will be 4 when we compile and fit our model for validation\n",
        "np.random.seed(11111)\n",
        "msk = np.random.rand(len(final_car)) < 0.72\n",
        "train_total = final_car[msk]\n",
        "test_total = final_car[~msk]\n"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JSjX5UckTu1_",
        "outputId": "c63ba8a3-6f4a-4e45-9bd7-529452ccbfac"
      },
      "source": [
        "#check the length of our test and train datasets\n",
        "print(len(train_total))\n",
        "print(len(test_total))\n"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "141\n",
            "64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 379
        },
        "id": "a4njPsfOfLJP",
        "outputId": "6d979919-c70b-4503-dc3a-2096f4d979b3"
      },
      "source": [
        "train_total.head(10)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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",
              "      <th>symboling_-2</th>\n",
              "      <th>symboling_-1</th>\n",
              "      <th>symboling_0</th>\n",
              "      <th>symboling_1</th>\n",
              "      <th>symboling_2</th>\n",
              "      <th>symboling_3</th>\n",
              "      <th>fueltype_diesel</th>\n",
              "      <th>fueltype_gas</th>\n",
              "      <th>aspiration_std</th>\n",
              "      <th>aspiration_turbo</th>\n",
              "      <th>doornumber_four</th>\n",
              "      <th>doornumber_two</th>\n",
              "      <th>carbody_convertible</th>\n",
              "      <th>carbody_hardtop</th>\n",
              "      <th>carbody_hatchback</th>\n",
              "      <th>carbody_sedan</th>\n",
              "      <th>carbody_wagon</th>\n",
              "      <th>drivewheel_4wd</th>\n",
              "      <th>drivewheel_fwd</th>\n",
              "      <th>drivewheel_rwd</th>\n",
              "      <th>enginelocation_front</th>\n",
              "      <th>enginelocation_rear</th>\n",
              "      <th>enginetype_dohc</th>\n",
              "      <th>enginetype_dohcv</th>\n",
              "      <th>enginetype_l</th>\n",
              "      <th>enginetype_ohc</th>\n",
              "      <th>enginetype_ohcf</th>\n",
              "      <th>enginetype_ohcv</th>\n",
              "      <th>enginetype_rotor</th>\n",
              "      <th>cylindernumber_eight</th>\n",
              "      <th>cylindernumber_five</th>\n",
              "      <th>cylindernumber_four</th>\n",
              "      <th>cylindernumber_six</th>\n",
              "      <th>cylindernumber_three</th>\n",
              "      <th>cylindernumber_twelve</th>\n",
              "      <th>cylindernumber_two</th>\n",
              "      <th>fuelsystem_1bbl</th>\n",
              "      <th>fuelsystem_2bbl</th>\n",
              "      <th>fuelsystem_4bbl</th>\n",
              "      <th>fuelsystem_idi</th>\n",
              "      <th>fuelsystem_mfi</th>\n",
              "      <th>fuelsystem_mpfi</th>\n",
              "      <th>fuelsystem_spdi</th>\n",
              "      <th>fuelsystem_spfi</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\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>16500.000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\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>16500.000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\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>13950.000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\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>17450.000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>99.8</td>\n",
              "      <td>177.3</td>\n",
              "      <td>66.3</td>\n",
              "      <td>53.1</td>\n",
              "      <td>2507</td>\n",
              "      <td>136</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3.40</td>\n",
              "      <td>8.5</td>\n",
              "      <td>110</td>\n",
              "      <td>5500</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>15250.000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>105.8</td>\n",
              "      <td>192.7</td>\n",
              "      <td>71.4</td>\n",
              "      <td>55.7</td>\n",
              "      <td>2844</td>\n",
              "      <td>136</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3.40</td>\n",
              "      <td>8.5</td>\n",
              "      <td>110</td>\n",
              "      <td>5500</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>17710.000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>105.8</td>\n",
              "      <td>192.7</td>\n",
              "      <td>71.4</td>\n",
              "      <td>55.7</td>\n",
              "      <td>2954</td>\n",
              "      <td>136</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3.40</td>\n",
              "      <td>8.5</td>\n",
              "      <td>110</td>\n",
              "      <td>5500</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>18920.000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>105.8</td>\n",
              "      <td>192.7</td>\n",
              "      <td>71.4</td>\n",
              "      <td>55.9</td>\n",
              "      <td>3086</td>\n",
              "      <td>131</td>\n",
              "      <td>3.13</td>\n",
              "      <td>3.40</td>\n",
              "      <td>8.3</td>\n",
              "      <td>140</td>\n",
              "      <td>5500</td>\n",
              "      <td>17</td>\n",
              "      <td>20</td>\n",
              "      <td>23875.000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>99.5</td>\n",
              "      <td>178.2</td>\n",
              "      <td>67.9</td>\n",
              "      <td>52.0</td>\n",
              "      <td>3053</td>\n",
              "      <td>131</td>\n",
              "      <td>3.13</td>\n",
              "      <td>3.40</td>\n",
              "      <td>7.0</td>\n",
              "      <td>160</td>\n",
              "      <td>5500</td>\n",
              "      <td>16</td>\n",
              "      <td>22</td>\n",
              "      <td>17859.167</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>101.2</td>\n",
              "      <td>176.8</td>\n",
              "      <td>64.8</td>\n",
              "      <td>54.3</td>\n",
              "      <td>2395</td>\n",
              "      <td>108</td>\n",
              "      <td>3.50</td>\n",
              "      <td>2.80</td>\n",
              "      <td>8.8</td>\n",
              "      <td>101</td>\n",
              "      <td>5800</td>\n",
              "      <td>23</td>\n",
              "      <td>29</td>\n",
              "      <td>16925.000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    wheelbase  carlength  ...  fuelsystem_spdi  fuelsystem_spfi\n",
              "1        88.6      168.8  ...                0                0\n",
              "2        94.5      171.2  ...                0                0\n",
              "3        99.8      176.6  ...                0                0\n",
              "4        99.4      176.6  ...                0                0\n",
              "5        99.8      177.3  ...                0                0\n",
              "6       105.8      192.7  ...                0                0\n",
              "7       105.8      192.7  ...                0                0\n",
              "8       105.8      192.7  ...                0                0\n",
              "9        99.5      178.2  ...                0                0\n",
              "11      101.2      176.8  ...                0                0\n",
              "\n",
              "[10 rows x 58 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BeYOhn1Eiams",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "outputId": "947cd4a0-da26-480c-a213-163ebab77e93"
      },
      "source": [
        "# check statistical overview if there are some outliers and abnormal values\n",
        "train_total.describe()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></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",
              "      <th>symboling_-2</th>\n",
              "      <th>symboling_-1</th>\n",
              "      <th>symboling_0</th>\n",
              "      <th>symboling_1</th>\n",
              "      <th>symboling_2</th>\n",
              "      <th>symboling_3</th>\n",
              "      <th>fueltype_diesel</th>\n",
              "      <th>fueltype_gas</th>\n",
              "      <th>aspiration_std</th>\n",
              "      <th>aspiration_turbo</th>\n",
              "      <th>doornumber_four</th>\n",
              "      <th>doornumber_two</th>\n",
              "      <th>carbody_convertible</th>\n",
              "      <th>carbody_hardtop</th>\n",
              "      <th>carbody_hatchback</th>\n",
              "      <th>carbody_sedan</th>\n",
              "      <th>carbody_wagon</th>\n",
              "      <th>drivewheel_4wd</th>\n",
              "      <th>drivewheel_fwd</th>\n",
              "      <th>drivewheel_rwd</th>\n",
              "      <th>enginelocation_front</th>\n",
              "      <th>enginelocation_rear</th>\n",
              "      <th>enginetype_dohc</th>\n",
              "      <th>enginetype_dohcv</th>\n",
              "      <th>enginetype_l</th>\n",
              "      <th>enginetype_ohc</th>\n",
              "      <th>enginetype_ohcf</th>\n",
              "      <th>enginetype_ohcv</th>\n",
              "      <th>enginetype_rotor</th>\n",
              "      <th>cylindernumber_eight</th>\n",
              "      <th>cylindernumber_five</th>\n",
              "      <th>cylindernumber_four</th>\n",
              "      <th>cylindernumber_six</th>\n",
              "      <th>cylindernumber_three</th>\n",
              "      <th>cylindernumber_twelve</th>\n",
              "      <th>cylindernumber_two</th>\n",
              "      <th>fuelsystem_1bbl</th>\n",
              "      <th>fuelsystem_2bbl</th>\n",
              "      <th>fuelsystem_4bbl</th>\n",
              "      <th>fuelsystem_idi</th>\n",
              "      <th>fuelsystem_mfi</th>\n",
              "      <th>fuelsystem_mpfi</th>\n",
              "      <th>fuelsystem_spdi</th>\n",
              "      <th>fuelsystem_spfi</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.0</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.00000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.0</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.0</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>141.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>98.692199</td>\n",
              "      <td>173.658156</td>\n",
              "      <td>65.875887</td>\n",
              "      <td>53.648227</td>\n",
              "      <td>2546.787234</td>\n",
              "      <td>125.666667</td>\n",
              "      <td>3.324184</td>\n",
              "      <td>3.256809</td>\n",
              "      <td>10.070355</td>\n",
              "      <td>103.702128</td>\n",
              "      <td>5143.971631</td>\n",
              "      <td>25.113475</td>\n",
              "      <td>30.581560</td>\n",
              "      <td>13379.132390</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.120567</td>\n",
              "      <td>0.304965</td>\n",
              "      <td>0.276596</td>\n",
              "      <td>0.156028</td>\n",
              "      <td>0.141844</td>\n",
              "      <td>0.092199</td>\n",
              "      <td>0.907801</td>\n",
              "      <td>0.801418</td>\n",
              "      <td>0.198582</td>\n",
              "      <td>0.553191</td>\n",
              "      <td>0.446809</td>\n",
              "      <td>0.035461</td>\n",
              "      <td>0.042553</td>\n",
              "      <td>0.347518</td>\n",
              "      <td>0.446809</td>\n",
              "      <td>0.12766</td>\n",
              "      <td>0.056738</td>\n",
              "      <td>0.581560</td>\n",
              "      <td>0.361702</td>\n",
              "      <td>0.985816</td>\n",
              "      <td>0.014184</td>\n",
              "      <td>0.063830</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.049645</td>\n",
              "      <td>0.723404</td>\n",
              "      <td>0.078014</td>\n",
              "      <td>0.056738</td>\n",
              "      <td>0.028369</td>\n",
              "      <td>0.014184</td>\n",
              "      <td>0.063830</td>\n",
              "      <td>0.765957</td>\n",
              "      <td>0.120567</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.007092</td>\n",
              "      <td>0.028369</td>\n",
              "      <td>0.056738</td>\n",
              "      <td>0.326241</td>\n",
              "      <td>0.021277</td>\n",
              "      <td>0.092199</td>\n",
              "      <td>0.007092</td>\n",
              "      <td>0.453901</td>\n",
              "      <td>0.035461</td>\n",
              "      <td>0.007092</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>6.005665</td>\n",
              "      <td>12.320089</td>\n",
              "      <td>2.188604</td>\n",
              "      <td>2.508204</td>\n",
              "      <td>529.769152</td>\n",
              "      <td>41.733451</td>\n",
              "      <td>0.266123</td>\n",
              "      <td>0.296387</td>\n",
              "      <td>3.868579</td>\n",
              "      <td>38.424275</td>\n",
              "      <td>474.472458</td>\n",
              "      <td>6.509435</td>\n",
              "      <td>6.734937</td>\n",
              "      <td>8189.494568</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.326785</td>\n",
              "      <td>0.462034</td>\n",
              "      <td>0.448910</td>\n",
              "      <td>0.364176</td>\n",
              "      <td>0.350134</td>\n",
              "      <td>0.290337</td>\n",
              "      <td>0.290337</td>\n",
              "      <td>0.400354</td>\n",
              "      <td>0.400354</td>\n",
              "      <td>0.498935</td>\n",
              "      <td>0.498935</td>\n",
              "      <td>0.185601</td>\n",
              "      <td>0.202567</td>\n",
              "      <td>0.477879</td>\n",
              "      <td>0.498935</td>\n",
              "      <td>0.33490</td>\n",
              "      <td>0.232165</td>\n",
              "      <td>0.495062</td>\n",
              "      <td>0.482206</td>\n",
              "      <td>0.118672</td>\n",
              "      <td>0.118672</td>\n",
              "      <td>0.245321</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.217986</td>\n",
              "      <td>0.448910</td>\n",
              "      <td>0.269150</td>\n",
              "      <td>0.232165</td>\n",
              "      <td>0.166616</td>\n",
              "      <td>0.118672</td>\n",
              "      <td>0.245321</td>\n",
              "      <td>0.424908</td>\n",
              "      <td>0.326785</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.084215</td>\n",
              "      <td>0.166616</td>\n",
              "      <td>0.232165</td>\n",
              "      <td>0.470508</td>\n",
              "      <td>0.144819</td>\n",
              "      <td>0.290337</td>\n",
              "      <td>0.084215</td>\n",
              "      <td>0.499645</td>\n",
              "      <td>0.185601</td>\n",
              "      <td>0.084215</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>86.600000</td>\n",
              "      <td>144.600000</td>\n",
              "      <td>61.800000</td>\n",
              "      <td>47.800000</td>\n",
              "      <td>1713.000000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>2.680000</td>\n",
              "      <td>2.190000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>55.000000</td>\n",
              "      <td>4150.000000</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>5118.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>94.500000</td>\n",
              "      <td>166.300000</td>\n",
              "      <td>64.000000</td>\n",
              "      <td>51.600000</td>\n",
              "      <td>2128.000000</td>\n",
              "      <td>97.000000</td>\n",
              "      <td>3.150000</td>\n",
              "      <td>3.150000</td>\n",
              "      <td>8.500000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>4800.000000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>7689.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>96.500000</td>\n",
              "      <td>172.400000</td>\n",
              "      <td>65.400000</td>\n",
              "      <td>53.900000</td>\n",
              "      <td>2410.000000</td>\n",
              "      <td>110.000000</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>10245.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>102.400000</td>\n",
              "      <td>180.300000</td>\n",
              "      <td>66.600000</td>\n",
              "      <td>55.500000</td>\n",
              "      <td>2952.000000</td>\n",
              "      <td>141.000000</td>\n",
              "      <td>3.580000</td>\n",
              "      <td>3.400000</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>16695.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>115.600000</td>\n",
              "      <td>202.600000</td>\n",
              "      <td>72.000000</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>262.000000</td>\n",
              "      <td>6600.000000</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>54.000000</td>\n",
              "      <td>45400.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.00000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        wheelbase   carlength  ...  fuelsystem_spdi  fuelsystem_spfi\n",
              "count  141.000000  141.000000  ...       141.000000       141.000000\n",
              "mean    98.692199  173.658156  ...         0.035461         0.007092\n",
              "std      6.005665   12.320089  ...         0.185601         0.084215\n",
              "min     86.600000  144.600000  ...         0.000000         0.000000\n",
              "25%     94.500000  166.300000  ...         0.000000         0.000000\n",
              "50%     96.500000  172.400000  ...         0.000000         0.000000\n",
              "75%    102.400000  180.300000  ...         0.000000         0.000000\n",
              "max    115.600000  202.600000  ...         1.000000         1.000000\n",
              "\n",
              "[8 rows x 58 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Iwv0k5MXkjiU",
        "outputId": "a1e93d3b-5be1-4b31-f6f1-57a9b5e3c542"
      },
      "source": [
        "print(train_total.dtypes)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "wheelbase                float64\n",
            "carlength                float64\n",
            "carwidth                 float64\n",
            "carheight                float64\n",
            "curbweight                 int64\n",
            "enginesize                 int64\n",
            "boreratio                float64\n",
            "stroke                   float64\n",
            "compressionratio         float64\n",
            "horsepower                 int64\n",
            "peakrpm                    int64\n",
            "citympg                    int64\n",
            "highwaympg                 int64\n",
            "price                    float64\n",
            "symboling_-2               uint8\n",
            "symboling_-1               uint8\n",
            "symboling_0                uint8\n",
            "symboling_1                uint8\n",
            "symboling_2                uint8\n",
            "symboling_3                uint8\n",
            "fueltype_diesel            uint8\n",
            "fueltype_gas               uint8\n",
            "aspiration_std             uint8\n",
            "aspiration_turbo           uint8\n",
            "doornumber_four            uint8\n",
            "doornumber_two             uint8\n",
            "carbody_convertible        uint8\n",
            "carbody_hardtop            uint8\n",
            "carbody_hatchback          uint8\n",
            "carbody_sedan              uint8\n",
            "carbody_wagon              uint8\n",
            "drivewheel_4wd             uint8\n",
            "drivewheel_fwd             uint8\n",
            "drivewheel_rwd             uint8\n",
            "enginelocation_front       uint8\n",
            "enginelocation_rear        uint8\n",
            "enginetype_dohc            uint8\n",
            "enginetype_dohcv           uint8\n",
            "enginetype_l               uint8\n",
            "enginetype_ohc             uint8\n",
            "enginetype_ohcf            uint8\n",
            "enginetype_ohcv            uint8\n",
            "enginetype_rotor           uint8\n",
            "cylindernumber_eight       uint8\n",
            "cylindernumber_five        uint8\n",
            "cylindernumber_four        uint8\n",
            "cylindernumber_six         uint8\n",
            "cylindernumber_three       uint8\n",
            "cylindernumber_twelve      uint8\n",
            "cylindernumber_two         uint8\n",
            "fuelsystem_1bbl            uint8\n",
            "fuelsystem_2bbl            uint8\n",
            "fuelsystem_4bbl            uint8\n",
            "fuelsystem_idi             uint8\n",
            "fuelsystem_mfi             uint8\n",
            "fuelsystem_mpfi            uint8\n",
            "fuelsystem_spdi            uint8\n",
            "fuelsystem_spfi            uint8\n",
            "dtype: object\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UMVbWuxTzEUh"
      },
      "source": [
        "# get our price labels and store in another dataframe\n",
        "train_label = train_total.loc[:,'price']\n",
        "test_label = test_total.loc[:,'price']"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ok93gWC0V7RC",
        "outputId": "5e358f7e-e9c1-4024-9fa5-375e7be5e359"
      },
      "source": [
        "train_label"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1      16500.0\n",
              "2      16500.0\n",
              "3      13950.0\n",
              "4      17450.0\n",
              "5      15250.0\n",
              "        ...   \n",
              "200    16845.0\n",
              "201    19045.0\n",
              "202    21485.0\n",
              "203    22470.0\n",
              "204    22625.0\n",
              "Name: price, Length: 141, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0pj0hGliz6ld"
      },
      "source": [
        "# drop price from oroginal training and test dataset , as price is not needed there\n",
        "test_data= test_total.drop(columns = ['price'])\n",
        "train_data= train_total.drop(columns = ['price'])"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7uw8yz0e1RjS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "da219927-e4a0-4800-c4f3-66dbba593d81"
      },
      "source": [
        "train_data.shape"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(141, 57)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "id": "ic0-eZgDZjsV",
        "outputId": "1cc6af6b-f5f1-4577-b6d6-c2a89b0f09b1"
      },
      "source": [
        "train_data"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>symboling_-2</th>\n",
              "      <th>symboling_-1</th>\n",
              "      <th>symboling_0</th>\n",
              "      <th>symboling_1</th>\n",
              "      <th>symboling_2</th>\n",
              "      <th>symboling_3</th>\n",
              "      <th>fueltype_diesel</th>\n",
              "      <th>fueltype_gas</th>\n",
              "      <th>aspiration_std</th>\n",
              "      <th>aspiration_turbo</th>\n",
              "      <th>doornumber_four</th>\n",
              "      <th>doornumber_two</th>\n",
              "      <th>carbody_convertible</th>\n",
              "      <th>carbody_hardtop</th>\n",
              "      <th>carbody_hatchback</th>\n",
              "      <th>carbody_sedan</th>\n",
              "      <th>carbody_wagon</th>\n",
              "      <th>drivewheel_4wd</th>\n",
              "      <th>drivewheel_fwd</th>\n",
              "      <th>drivewheel_rwd</th>\n",
              "      <th>enginelocation_front</th>\n",
              "      <th>enginelocation_rear</th>\n",
              "      <th>enginetype_dohc</th>\n",
              "      <th>enginetype_dohcv</th>\n",
              "      <th>enginetype_l</th>\n",
              "      <th>enginetype_ohc</th>\n",
              "      <th>enginetype_ohcf</th>\n",
              "      <th>enginetype_ohcv</th>\n",
              "      <th>enginetype_rotor</th>\n",
              "      <th>cylindernumber_eight</th>\n",
              "      <th>cylindernumber_five</th>\n",
              "      <th>cylindernumber_four</th>\n",
              "      <th>cylindernumber_six</th>\n",
              "      <th>cylindernumber_three</th>\n",
              "      <th>cylindernumber_twelve</th>\n",
              "      <th>cylindernumber_two</th>\n",
              "      <th>fuelsystem_1bbl</th>\n",
              "      <th>fuelsystem_2bbl</th>\n",
              "      <th>fuelsystem_4bbl</th>\n",
              "      <th>fuelsystem_idi</th>\n",
              "      <th>fuelsystem_mfi</th>\n",
              "      <th>fuelsystem_mpfi</th>\n",
              "      <th>fuelsystem_spdi</th>\n",
              "      <th>fuelsystem_spfi</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\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>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\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>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\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>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\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>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>99.8</td>\n",
              "      <td>177.3</td>\n",
              "      <td>66.3</td>\n",
              "      <td>53.1</td>\n",
              "      <td>2507</td>\n",
              "      <td>136</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3.40</td>\n",
              "      <td>8.5</td>\n",
              "      <td>110</td>\n",
              "      <td>5500</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <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>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>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\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>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\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>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\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>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\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>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>141 rows × 57 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     wheelbase  carlength  ...  fuelsystem_spdi  fuelsystem_spfi\n",
              "1         88.6      168.8  ...                0                0\n",
              "2         94.5      171.2  ...                0                0\n",
              "3         99.8      176.6  ...                0                0\n",
              "4         99.4      176.6  ...                0                0\n",
              "5         99.8      177.3  ...                0                0\n",
              "..         ...        ...  ...              ...              ...\n",
              "200      109.1      188.8  ...                0                0\n",
              "201      109.1      188.8  ...                0                0\n",
              "202      109.1      188.8  ...                0                0\n",
              "203      109.1      188.8  ...                0                0\n",
              "204      109.1      188.8  ...                0                0\n",
              "\n",
              "[141 rows x 57 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jTXSdXZs5InD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c56465b7-3510-4d4b-fc23-ae864404289f"
      },
      "source": [
        "#get indices of the columns so that we can know how many columns we have to normalize, as catagorical columns which we\n",
        "# have added with onehot encoding, do not need to be normalized.. normalizing will be done in next cell\n",
        "{train_data.columns.get_loc(c): c for idx, c in enumerate(train_data.columns)}"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{0: 'wheelbase',\n",
              " 1: 'carlength',\n",
              " 2: 'carwidth',\n",
              " 3: 'carheight',\n",
              " 4: 'curbweight',\n",
              " 5: 'enginesize',\n",
              " 6: 'boreratio',\n",
              " 7: 'stroke',\n",
              " 8: 'compressionratio',\n",
              " 9: 'horsepower',\n",
              " 10: 'peakrpm',\n",
              " 11: 'citympg',\n",
              " 12: 'highwaympg',\n",
              " 13: 'symboling_-2',\n",
              " 14: 'symboling_-1',\n",
              " 15: 'symboling_0',\n",
              " 16: 'symboling_1',\n",
              " 17: 'symboling_2',\n",
              " 18: 'symboling_3',\n",
              " 19: 'fueltype_diesel',\n",
              " 20: 'fueltype_gas',\n",
              " 21: 'aspiration_std',\n",
              " 22: 'aspiration_turbo',\n",
              " 23: 'doornumber_four',\n",
              " 24: 'doornumber_two',\n",
              " 25: 'carbody_convertible',\n",
              " 26: 'carbody_hardtop',\n",
              " 27: 'carbody_hatchback',\n",
              " 28: 'carbody_sedan',\n",
              " 29: 'carbody_wagon',\n",
              " 30: 'drivewheel_4wd',\n",
              " 31: 'drivewheel_fwd',\n",
              " 32: 'drivewheel_rwd',\n",
              " 33: 'enginelocation_front',\n",
              " 34: 'enginelocation_rear',\n",
              " 35: 'enginetype_dohc',\n",
              " 36: 'enginetype_dohcv',\n",
              " 37: 'enginetype_l',\n",
              " 38: 'enginetype_ohc',\n",
              " 39: 'enginetype_ohcf',\n",
              " 40: 'enginetype_ohcv',\n",
              " 41: 'enginetype_rotor',\n",
              " 42: 'cylindernumber_eight',\n",
              " 43: 'cylindernumber_five',\n",
              " 44: 'cylindernumber_four',\n",
              " 45: 'cylindernumber_six',\n",
              " 46: 'cylindernumber_three',\n",
              " 47: 'cylindernumber_twelve',\n",
              " 48: 'cylindernumber_two',\n",
              " 49: 'fuelsystem_1bbl',\n",
              " 50: 'fuelsystem_2bbl',\n",
              " 51: 'fuelsystem_4bbl',\n",
              " 52: 'fuelsystem_idi',\n",
              " 53: 'fuelsystem_mfi',\n",
              " 54: 'fuelsystem_mpfi',\n",
              " 55: 'fuelsystem_spdi',\n",
              " 56: 'fuelsystem_spfi'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1h5vhggTyRyw"
      },
      "source": [
        "## we normalize data because data has big vlaues in decimal and it will worsen performance of our model, may overfit \n",
        "## or  we may face hardware resource high usage\n",
        "# we will apply the formula normalized_train_data = (train_data - mean)/ stadrad_deviation\n",
        "## firt take mean of training, then subtract mean from each value of the array slice train_data.iloc[:,0:13]\n",
        "mean = train_data.iloc[:,0:13].mean(axis=0) # taking the mean of \n",
        "train_data.iloc[:,0:13] -= mean\n",
        "std = train_data.iloc[:,0:13].std(axis=0)\n",
        "train_data.iloc[:,0:13] /= std\n",
        "test_data.iloc[:,0:13] -= mean\n",
        "test_data.iloc[:,0:13] /= std\n",
        "\n"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XdXge3xhAyiN"
      },
      "source": [
        "# x = (y - z)/ std"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CZYfOs0cfaGE"
      },
      "source": [
        "mean_label = train_label.mean()\n",
        "train_label -= mean_label\n",
        "std_label = train_label.std()\n",
        "train_label /= std_label\n",
        "test_label -= mean_label\n",
        "test_label /= std_label\n"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2mc7B1amLmsx",
        "outputId": "b8bfa4f6-1783-4a81-dc77-3a96a20c9e8e"
      },
      "source": [
        "print(mean_label)"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "13379.132390070921\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g8uIRUHEw7g4",
        "outputId": "04bd391e-6214-4e35-e361-62981ec71d76"
      },
      "source": [
        "test_label"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      0.014148\n",
              "10     0.372534\n",
              "14     1.365880\n",
              "15     2.122337\n",
              "18    -1.004718\n",
              "         ...   \n",
              "192    0.056886\n",
              "193   -0.132991\n",
              "194   -0.053621\n",
              "196    0.318196\n",
              "198    0.615529\n",
              "Name: price, Length: 64, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZwYKROqCyWwi",
        "outputId": "96a2b09e-c6a9-4698-8566-e03d665940a8"
      },
      "source": [
        "train_data.shape"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(141, 57)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ejyRo91P9Klh"
      },
      "source": [
        "#store in numpy array"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eLTpt0qn-R5y"
      },
      "source": [
        "test = np.array(test_data.iloc[:])"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6ym52Tun-vhn"
      },
      "source": [
        "train = np.array(train_data.iloc[:])"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TnFGfxGn_d1b"
      },
      "source": [
        "test_l= np.array(test_label.astype('float32'))"
      ],
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kklQZ0za_qZb"
      },
      "source": [
        "train_l= np.array(train_label.astype('float32'))"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mVbXDcGe5cY2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "15a8daa8-57a1-4dd2-d091-9ce26f18140c"
      },
      "source": [
        "train.shape\n"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(141, 57)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ArLkQAzx9W0f"
      },
      "source": [
        ""
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MS0mDY0d9y3Q"
      },
      "source": [
        ""
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Mm416iVz953_"
      },
      "source": [
        "\n",
        "# Models section\n",
        "```\n",
        "#WE will configure different models here according to relu, tanh , regularization, dropout etc..\n",
        "```\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EqOJjh8n8fMU"
      },
      "source": [
        "# we are passing activation function as a parameter here so that we can call this function with tanh or relu while\n",
        "# fitting and training the model\n",
        "from keras import models\n",
        "from keras import layers\n",
        "def build_model(act):\n",
        "  model = models.Sequential()\n",
        "  model.add(layers.Dense(10, activation= act,input_shape=(train.shape[1],)))\n",
        "  model.add(layers.Dense(8, activation= act))\n",
        "  model.add(layers.Dense(6, activation= act))\n",
        "  model.add(layers.Dense(1))\n",
        "  model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])\n",
        "  return model"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZKs2Axd19Rsx",
        "outputId": "7686d9a1-b37f-478f-9895-5c011a789c63"
      },
      "source": [
        "build_model('relu').summary()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense (Dense)                (None, 10)                580       \n",
            "_________________________________________________________________\n",
            "dense_1 (Dense)              (None, 8)                 88        \n",
            "_________________________________________________________________\n",
            "dense_2 (Dense)              (None, 6)                 54        \n",
            "_________________________________________________________________\n",
            "dense_3 (Dense)              (None, 1)                 7         \n",
            "=================================================================\n",
            "Total params: 729\n",
            "Trainable params: 729\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ShTLMMUPWE2E",
        "outputId": "36d73732-7189-4993-b355-a06da4e820fe"
      },
      "source": [
        "build_model('tanh').summary()"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential_1\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense_4 (Dense)              (None, 10)                580       \n",
            "_________________________________________________________________\n",
            "dense_5 (Dense)              (None, 8)                 88        \n",
            "_________________________________________________________________\n",
            "dense_6 (Dense)              (None, 6)                 54        \n",
            "_________________________________________________________________\n",
            "dense_7 (Dense)              (None, 1)                 7         \n",
            "=================================================================\n",
            "Total params: 729\n",
            "Trainable params: 729\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iLNbzXjKqGSw"
      },
      "source": [
        "# Regularized model\n",
        "from keras import regularizers\n",
        "def build_model_regular(act):\n",
        "  model = models.Sequential()\n",
        "  model.add(layers.Dense(10, activation= act,kernel_regularizer= regularizers.l1_l2(l1=0.001, l2=0.001),input_shape=(train.shape[1],)))\n",
        "  model.add(layers.Dense(8, activation= act,kernel_regularizer= regularizers.l1_l2(l1=0.001, l2=0.001)))\n",
        "  model.add(layers.Dense(6, activation= act,kernel_regularizer= regularizers.l1_l2(l1=0.001, l2=0.001)))\n",
        "  model.add(layers.Dense(1))\n",
        "  model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])\n",
        "  return model"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "afnNh94NrncJ",
        "outputId": "3925b4b0-fce7-44f4-e6bc-64cf460e0d72"
      },
      "source": [
        "build_model_regular('tanh').summary()"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential_2\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense_8 (Dense)              (None, 10)                580       \n",
            "_________________________________________________________________\n",
            "dense_9 (Dense)              (None, 8)                 88        \n",
            "_________________________________________________________________\n",
            "dense_10 (Dense)             (None, 6)                 54        \n",
            "_________________________________________________________________\n",
            "dense_11 (Dense)             (None, 1)                 7         \n",
            "=================================================================\n",
            "Total params: 729\n",
            "Trainable params: 729\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hKOI8TLD1SHd"
      },
      "source": [
        "# dropout model\n",
        "from keras import regularizers\n",
        "def build_model_drop(act):\n",
        "  model = models.Sequential()\n",
        "  model.add(layers.Dense(10, activation= act,input_shape=(train.shape[1],)))\n",
        "  model.add(layers.Dropout(0.1))\n",
        "  model.add(layers.Dense(8, activation= act))\n",
        "  model.add(layers.Dropout(0.1))\n",
        "  model.add(layers.Dense(6, activation= act))\n",
        "  model.add(layers.Dropout(0.1))\n",
        "  model.add(layers.Dense(1))\n",
        "  model.compile(optimizer='rmsprop', loss='mse', metrics=['mae'])\n",
        "  return model"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YwAm7RMr_eMa"
      },
      "source": [
        "# K Fold validation section\n",
        "## here we will use len(train)//k to make 141//4 = 36 rows for validation in each validation test and collect the validation scores for relu , tanh , regularization , and dropout"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hTizsf6znpb7",
        "outputId": "59413768-3a0c-4e54-b675-7f3fec51a346"
      },
      "source": [
        "#k fold validation with relu\n",
        "# 141/4\n",
        "import numpy as np\n",
        "k =  4\n",
        "num_val_samples = len(train) // k\n",
        "num_epochs = 100\n",
        "all_scores_relu = []\n",
        "for i in range(k):\n",
        "  print('processing fold #', i)\n",
        "  val_data = train[i * num_val_samples: (i + 1) * num_val_samples]\n",
        "  val_targets = train_l[i * num_val_samples: (i + 1) * num_val_samples]\n",
        "  partial_train_data = np.concatenate([train[:i * num_val_samples],train[(i + 1) * num_val_samples:]],  axis=0)\n",
        "  # print(partial_train_data)\n",
        "  partial_train_targets = np.concatenate([train_l[:i * num_val_samples],train_l[(i + 1) * num_val_samples:]],axis=0)\n",
        "  model = build_model('relu')\n",
        "  model.fit(partial_train_data, partial_train_targets,epochs=num_epochs, batch_size=1, verbose=0)\n",
        "  val_mse, val_mae = model.evaluate(val_data, val_targets, verbose=0)\n",
        "  all_scores_relu.append(val_mae)\n"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "processing fold # 0\n",
            "processing fold # 1\n",
            "processing fold # 2\n",
            "processing fold # 3\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HaXgBohaz4WI",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6aa83b4c-b606-481c-ff74-332f31453fde"
      },
      "source": [
        "# 141/4\n",
        "#k fold validation with tanh\n",
        "import numpy as np\n",
        "k =  4\n",
        "num_val_samples = len(train) // k\n",
        "num_epochs = 100\n",
        "all_scores_tanh = []\n",
        "for i in range(k):\n",
        "  print('processing fold #', i)\n",
        "  val_data = train[i * num_val_samples: (i + 1) * num_val_samples]\n",
        "  val_targets = train_l[i * num_val_samples: (i + 1) * num_val_samples]\n",
        "  partial_train_data = np.concatenate([train[:i * num_val_samples],train[(i + 1) * num_val_samples:]],  axis=0)\n",
        "  # print(partial_train_data)\n",
        "  partial_train_targets = np.concatenate([train_l[:i * num_val_samples],train_l[(i + 1) * num_val_samples:]],axis=0)\n",
        "  model = build_model('tanh')\n",
        "  model.fit(partial_train_data, partial_train_targets,epochs=num_epochs, batch_size=1, verbose=0)\n",
        "  val_mse, val_mae = model.evaluate(val_data, val_targets, verbose=0)\n",
        "  all_scores_tanh.append(val_mae)"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "processing fold # 0\n",
            "WARNING:tensorflow:5 out of the last 9 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc20785a440> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "processing fold # 1\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc20422f560> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "processing fold # 2\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc20314d200> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "processing fold # 3\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc2207c8440> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SD6TuagJb54U",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fdc3fdf8-90b3-4fed-e8d5-3d293ab71062"
      },
      "source": [
        "#k-fold validtion with regularization\n",
        "import numpy as np\n",
        "k =  4\n",
        "num_val_samples = len(train) // k\n",
        "num_epochs = 100\n",
        "all_scores_regular = []\n",
        "for i in range(k):\n",
        "  print('processing fold #', i)\n",
        "  val_data = train[i * num_val_samples: (i + 1) * num_val_samples]\n",
        "  val_targets = train_l[i * num_val_samples: (i + 1) * num_val_samples]\n",
        "  partial_train_data = np.concatenate([train[:i * num_val_samples],train[(i + 1) * num_val_samples:]],  axis=0)\n",
        "  # print(partial_train_data)\n",
        "  partial_train_targets = np.concatenate([train_l[:i * num_val_samples],train_l[(i + 1) * num_val_samples:]],axis=0)\n",
        "  model = build_model_regular('relu')\n",
        "  model.fit(partial_train_data, partial_train_targets,epochs=num_epochs, batch_size=1, verbose=0)\n",
        "  val_mse, val_mae = model.evaluate(val_data, val_targets, verbose=0)\n",
        "  all_scores_regular.append(val_mae)"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "processing fold # 0\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc205d51b90> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "processing fold # 1\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc20923ca70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "processing fold # 2\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc20923c560> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "processing fold # 3\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc2089cf320> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B3ENBDAMrHtb",
        "outputId": "a9475d7f-c290-49f9-f6cb-e593b95f9049"
      },
      "source": [
        "#k-fold validtion with dropout\n",
        "import numpy as np\n",
        "k =  4\n",
        "num_val_samples = len(train) // k\n",
        "num_epochs = 100\n",
        "all_scores_drop = []\n",
        "for i in range(k):\n",
        "  print('processing fold #', i)\n",
        "  val_data = train[i * num_val_samples: (i + 1) * num_val_samples]\n",
        "  val_targets = train_l[i * num_val_samples: (i + 1) * num_val_samples]\n",
        "  partial_train_data = np.concatenate([train[:i * num_val_samples],train[(i + 1) * num_val_samples:]],  axis=0)\n",
        "  # print(partial_train_data)\n",
        "  partial_train_targets = np.concatenate([train_l[:i * num_val_samples],train_l[(i + 1) * num_val_samples:]],axis=0)\n",
        "  model = build_model_drop('relu')\n",
        "  model.fit(partial_train_data, partial_train_targets,epochs=num_epochs, batch_size=1, verbose=0)\n",
        "  val_mse, val_mae = model.evaluate(val_data, val_targets, verbose=0)\n",
        "  all_scores_drop.append(val_mae)"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "processing fold # 0\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc204266320> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "processing fold # 1\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc206654a70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "processing fold # 2\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc2065f2e60> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "processing fold # 3\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc220772e60> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hSlCIMtT_Gfd"
      },
      "source": [
        "# Scores\n",
        "## here we will see scores of all model which we have saved in the list during each training in above section"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "We_C7ivQsh8Y",
        "outputId": "f02b18a3-d641-4e11-bb85-9cab7a573634"
      },
      "source": [
        "all_scores_relu"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.39174214005470276,\n",
              " 0.2539793848991394,\n",
              " 0.44484013319015503,\n",
              " 0.33408406376838684]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y1gBTB5DrDA9",
        "outputId": "afaaeac4-b920-4f2a-8a72-695cd17823f3"
      },
      "source": [
        "all_scores_tanh"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.38517099618911743,\n",
              " 0.3186570405960083,\n",
              " 0.506381630897522,\n",
              " 0.36731037497520447]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Zf7O0WnN9bVF",
        "outputId": "391f37d2-f73b-4ecf-e1ee-0f21a05ed252"
      },
      "source": [
        "all_scores_regular"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.35633185505867004,\n",
              " 0.27310657501220703,\n",
              " 0.40894046425819397,\n",
              " 0.3828975558280945]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jB8LxbiI0cpx",
        "outputId": "f5b72182-48b8-430d-c1e5-6a7c51191bd5"
      },
      "source": [
        "all_scores_drop"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.3166130483150482,\n",
              " 0.35561612248420715,\n",
              " 0.4225921630859375,\n",
              " 0.3072565495967865]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wNxMnoqoAYd-"
      },
      "source": [
        "# training on the training data\n",
        "## here we will call each model separately from Models section and train on the training data and evaluate on the test data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VORrpehRb7UR",
        "outputId": "d0887b4e-55ae-4106-9a02-daf87756f87e"
      },
      "source": [
        "model_tanh = build_model('tanh')\n",
        "model_tanh.fit(train, train_l,epochs= 80, batch_size=1, verbose=0)\n",
        "test_mse_score, test_mae_score = model_tanh.evaluate(test, test_l)"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc206654680> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "2/2 [==============================] - 0s 12ms/step - loss: 0.1162 - mae: 0.2452\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ttydi9BzUnf5",
        "outputId": "3d3ea63b-1ed9-4494-ded6-9e528eb53a73"
      },
      "source": [
        "model_relu = build_model('relu')\n",
        "model_relu.fit(train, train_l,epochs= 80, batch_size=1, verbose=0)\n",
        "test_mse_score, test_mae_score = model_relu.evaluate(test, test_l)"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc205ceb0e0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "2/2 [==============================] - 0s 5ms/step - loss: 0.0856 - mae: 0.2298\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oZFYcfHftNlY",
        "outputId": "24cd85f8-ecee-4592-b84e-a55b79767613"
      },
      "source": [
        "model_regular = build_model_regular('relu')\n",
        "model_regular.fit(train, train_l,epochs= 80, batch_size=1, verbose=0)\n",
        "test_mse_score, test_mae_score = model_regular.evaluate(test, test_l)"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc20b018830> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "2/2 [==============================] - 0s 5ms/step - loss: 0.1110 - mae: 0.2152\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ELSZLSCb0g7c",
        "outputId": "6fe9947e-954b-4f7d-861e-0141322b7cbb"
      },
      "source": [
        "model_drop = build_model_drop('relu')\n",
        "model_drop.fit(train, train_l,epochs= 80, batch_size=1, verbose=0)\n",
        "test_mse_score, test_mae_score = model_drop.evaluate(test, test_l)"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7fc2053ee170> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "2/2 [==============================] - 0s 9ms/step - loss: 0.1053 - mae: 0.2571\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TV42POJyA-Na"
      },
      "source": [
        "# Prediction Section\n",
        "## here we will predict our prices of our test dataset with each model which we have trained in training section\n",
        "## Note that here we will use the reverse process of Normalization to retrieve our values of price in thousand of dollars i.e. x = (y - mean)/ std ==>> we will calculate( y = x * std + mean) and then we will compare it with our target values"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ofX9VqMVbhBC"
      },
      "source": [
        "x_tanh = model_tanh.predict(test[5].reshape(1,test.shape[1]))"
      ],
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eNBUOF1eK2DY",
        "outputId": "b82e6b64-0158-459f-dc99-0628b2a6994f"
      },
      "source": [
        "x_tanh * std_label + mean_label"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[7340.78]], dtype=float32)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "--R_tOuOcv67"
      },
      "source": [
        ""
      ],
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4Z0UyL_LOImw"
      },
      "source": [
        "x_relu = model_relu.predict(test[5].reshape(1,test.shape[1]))"
      ],
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NJnnzVWTb5MV",
        "outputId": "5c836112-6712-49cc-d921-73b53d98680f"
      },
      "source": [
        "x_relu * std_label + mean_label"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[7072.362]], dtype=float32)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2st4c4KwvdVA"
      },
      "source": [
        ""
      ],
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nlQRNOo0tb8J",
        "outputId": "09630ca7-f07f-4887-f88a-32e4897165c5"
      },
      "source": [
        "x_regular = model_regular.predict(test[5].reshape(1,test.shape[1]))\n",
        "x_regular * std_label + mean_label"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[6846.9126]], dtype=float32)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uW5Y65pP0qET",
        "outputId": "e24040f3-4bb4-4c78-a2ce-469ab64c8bcc"
      },
      "source": [
        "x_drop = model_drop.predict(test[5].reshape(1,test.shape[1]))\n",
        "x_drop * std_label + mean_label"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[8044.2397]], dtype=float32)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3bdo-oAvV7gt",
        "outputId": "ae1cb1c0-fe9f-4ca1-a18f-7532d5b5394c"
      },
      "source": [
        "test_l[5]* std_label + mean_label"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "7609.000199706916"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        }
      ]
    }
  ]
}