Multiple Linear Regression_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e1f253a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the libraries and packages\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import math as m\n",
    "import seaborn as sns\n",
    "sns.set_style(\"darkgrid\")\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.linear_model import LinearRegression,Ridge\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import r2_score,mean_squared_error\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "36734acf",
   "metadata": {},
   "outputs": [
    {
     "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>Id</th>\n",
       "      <th>Model</th>\n",
       "      <th>Price</th>\n",
       "      <th>Age_08_04</th>\n",
       "      <th>Mfg_Month</th>\n",
       "      <th>Mfg_Year</th>\n",
       "      <th>KM</th>\n",
       "      <th>Fuel_Type</th>\n",
       "      <th>HP</th>\n",
       "      <th>Met_Color</th>\n",
       "      <th>...</th>\n",
       "      <th>Central_Lock</th>\n",
       "      <th>Powered_Windows</th>\n",
       "      <th>Power_Steering</th>\n",
       "      <th>Radio</th>\n",
       "      <th>Mistlamps</th>\n",
       "      <th>Sport_Model</th>\n",
       "      <th>Backseat_Divider</th>\n",
       "      <th>Metallic_Rim</th>\n",
       "      <th>Radio_cassette</th>\n",
       "      <th>Tow_Bar</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n",
       "      <td>13500</td>\n",
       "      <td>23</td>\n",
       "      <td>10</td>\n",
       "      <td>2002</td>\n",
       "      <td>46986</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>90</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n",
       "      <td>13750</td>\n",
       "      <td>23</td>\n",
       "      <td>10</td>\n",
       "      <td>2002</td>\n",
       "      <td>72937</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>90</td>\n",
       "      <td>1</td>\n",
       "      <td>...</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>�TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n",
       "      <td>13950</td>\n",
       "      <td>24</td>\n",
       "      <td>9</td>\n",
       "      <td>2002</td>\n",
       "      <td>41711</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>90</td>\n",
       "      <td>1</td>\n",
       "      <td>...</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n",
       "      <td>14950</td>\n",
       "      <td>26</td>\n",
       "      <td>7</td>\n",
       "      <td>2002</td>\n",
       "      <td>48000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>...</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>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>TOYOTA Corolla 2.0 D4D HATCHB SOL 2/3-Doors</td>\n",
       "      <td>13750</td>\n",
       "      <td>30</td>\n",
       "      <td>3</td>\n",
       "      <td>2002</td>\n",
       "      <td>38500</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id                                           Model  Price  Age_08_04  \\\n",
       "0   1   TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13500         23   \n",
       "1   2   TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13750         23   \n",
       "2   3  �TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13950         24   \n",
       "3   4   TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  14950         26   \n",
       "4   5     TOYOTA Corolla 2.0 D4D HATCHB SOL 2/3-Doors  13750         30   \n",
       "\n",
       "   Mfg_Month  Mfg_Year     KM Fuel_Type  HP  Met_Color  ... Central_Lock  \\\n",
       "0         10      2002  46986    Diesel  90          1  ...            1   \n",
       "1         10      2002  72937    Diesel  90          1  ...            1   \n",
       "2          9      2002  41711    Diesel  90          1  ...            0   \n",
       "3          7      2002  48000    Diesel  90          0  ...            0   \n",
       "4          3      2002  38500    Diesel  90          0  ...            1   \n",
       "\n",
       "   Powered_Windows  Power_Steering  Radio  Mistlamps  Sport_Model  \\\n",
       "0                1               1      0          0            0   \n",
       "1                0               1      0          0            0   \n",
       "2                0               1      0          0            0   \n",
       "3                0               1      0          0            0   \n",
       "4                1               1      0          1            0   \n",
       "\n",
       "   Backseat_Divider  Metallic_Rim  Radio_cassette  Tow_Bar  \n",
       "0                 1             0               0        0  \n",
       "1                 1             0               0        0  \n",
       "2                 1             0               0        0  \n",
       "3                 1             0               0        0  \n",
       "4                 1             0               0        0  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Loading the dataset\n",
    "data = pd.read_csv(\"ToyotaCorolla.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e54db75e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Id                                           Model  Price  Age_08_04  \\\n",
      "0   1   TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13500         23   \n",
      "1   2   TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13750         23   \n",
      "2   3  �TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13950         24   \n",
      "3   4   TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  14950         26   \n",
      "4   5     TOYOTA Corolla 2.0 D4D HATCHB SOL 2/3-Doors  13750         30   \n",
      "\n",
      "   Mfg_Month  Mfg_Year     KM Fuel_Type  HP  Met_Color  ... Central_Lock  \\\n",
      "0         10      2002  46986    Diesel  90          1  ...            1   \n",
      "1         10      2002  72937    Diesel  90          1  ...            1   \n",
      "2          9      2002  41711    Diesel  90          1  ...            0   \n",
      "3          7      2002  48000    Diesel  90          0  ...            0   \n",
      "4          3      2002  38500    Diesel  90          0  ...            1   \n",
      "\n",
      "   Powered_Windows  Power_Steering  Radio  Mistlamps  Sport_Model  \\\n",
      "0                1               1      0          0            0   \n",
      "1                0               1      0          0            0   \n",
      "2                0               1      0          0            0   \n",
      "3                0               1      0          0            0   \n",
      "4                1               1      0          1            0   \n",
      "\n",
      "   Backseat_Divider  Metallic_Rim  Radio_cassette  Tow_Bar  \n",
      "0                 1             0               0        0  \n",
      "1                 1             0               0        0  \n",
      "2                 1             0               0        0  \n",
      "3                 1             0               0        0  \n",
      "4                 1             0               0        0  \n",
      "\n",
      "[5 rows x 38 columns]\n"
     ]
    }
   ],
   "source": [
    "# renaming the columns\n",
    "data=data.rename({ \"R&D Spend\":'R&D',\"Marketing Spend\":'marketing',\"Administration\":\"administration\",\"State\":\"state\",\"Profit\":\"profit\"},axis=1)\n",
    "print(data.head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5b746e51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id                  0\n",
       "Model               0\n",
       "Price               0\n",
       "Age_08_04           0\n",
       "Mfg_Month           0\n",
       "Mfg_Year            0\n",
       "KM                  0\n",
       "Fuel_Type           0\n",
       "HP                  0\n",
       "Met_Color           0\n",
       "Color               0\n",
       "Automatic           0\n",
       "cc                  0\n",
       "Doors               0\n",
       "Cylinders           0\n",
       "Gears               0\n",
       "Quarterly_Tax       0\n",
       "Weight              0\n",
       "Mfr_Guarantee       0\n",
       "BOVAG_Guarantee     0\n",
       "Guarantee_Period    0\n",
       "ABS                 0\n",
       "Airbag_1            0\n",
       "Airbag_2            0\n",
       "Airco               0\n",
       "Automatic_airco     0\n",
       "Boardcomputer       0\n",
       "CD_Player           0\n",
       "Central_Lock        0\n",
       "Powered_Windows     0\n",
       "Power_Steering      0\n",
       "Radio               0\n",
       "Mistlamps           0\n",
       "Sport_Model         0\n",
       "Backseat_Divider    0\n",
       "Metallic_Rim        0\n",
       "Radio_cassette      0\n",
       "Tow_Bar             0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking the missing values\n",
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2a8ad39f",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Id', 'Model', 'Price', 'Age_08_04', 'Mfg_Month', 'Mfg_Year', 'KM',\n",
      "       'Fuel_Type', 'HP', 'Met_Color', 'Color', 'Automatic', 'cc', 'Doors',\n",
      "       'Cylinders', 'Gears', 'Quarterly_Tax', 'Weight', 'Mfr_Guarantee',\n",
      "       'BOVAG_Guarantee', 'Guarantee_Period', 'ABS', 'Airbag_1', 'Airbag_2',\n",
      "       'Airco', 'Automatic_airco', 'Boardcomputer', 'CD_Player',\n",
      "       'Central_Lock', 'Powered_Windows', 'Power_Steering', 'Radio',\n",
      "       'Mistlamps', 'Sport_Model', 'Backseat_Divider', 'Metallic_Rim',\n",
      "       'Radio_cassette', 'Tow_Bar'],\n",
      "      dtype='object')\n",
      "Data types---\n",
      "==========================\n",
      "Id                   int64\n",
      "Model               object\n",
      "Price                int64\n",
      "Age_08_04            int64\n",
      "Mfg_Month            int64\n",
      "Mfg_Year             int64\n",
      "KM                   int64\n",
      "Fuel_Type           object\n",
      "HP                   int64\n",
      "Met_Color            int64\n",
      "Color               object\n",
      "Automatic            int64\n",
      "cc                   int64\n",
      "Doors                int64\n",
      "Cylinders            int64\n",
      "Gears                int64\n",
      "Quarterly_Tax        int64\n",
      "Weight               int64\n",
      "Mfr_Guarantee        int64\n",
      "BOVAG_Guarantee      int64\n",
      "Guarantee_Period     int64\n",
      "ABS                  int64\n",
      "Airbag_1             int64\n",
      "Airbag_2             int64\n",
      "Airco                int64\n",
      "Automatic_airco      int64\n",
      "Boardcomputer        int64\n",
      "CD_Player            int64\n",
      "Central_Lock         int64\n",
      "Powered_Windows      int64\n",
      "Power_Steering       int64\n",
      "Radio                int64\n",
      "Mistlamps            int64\n",
      "Sport_Model          int64\n",
      "Backseat_Divider     int64\n",
      "Metallic_Rim         int64\n",
      "Radio_cassette       int64\n",
      "Tow_Bar              int64\n",
      "dtype: object\n",
      "==========================\n",
      "Info---\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1436 entries, 0 to 1435\n",
      "Data columns (total 38 columns):\n",
      " #   Column            Non-Null Count  Dtype \n",
      "---  ------            --------------  ----- \n",
      " 0   Id                1436 non-null   int64 \n",
      " 1   Model             1436 non-null   object\n",
      " 2   Price             1436 non-null   int64 \n",
      " 3   Age_08_04         1436 non-null   int64 \n",
      " 4   Mfg_Month         1436 non-null   int64 \n",
      " 5   Mfg_Year          1436 non-null   int64 \n",
      " 6   KM                1436 non-null   int64 \n",
      " 7   Fuel_Type         1436 non-null   object\n",
      " 8   HP                1436 non-null   int64 \n",
      " 9   Met_Color         1436 non-null   int64 \n",
      " 10  Color             1436 non-null   object\n",
      " 11  Automatic         1436 non-null   int64 \n",
      " 12  cc                1436 non-null   int64 \n",
      " 13  Doors             1436 non-null   int64 \n",
      " 14  Cylinders         1436 non-null   int64 \n",
      " 15  Gears             1436 non-null   int64 \n",
      " 16  Quarterly_Tax     1436 non-null   int64 \n",
      " 17  Weight            1436 non-null   int64 \n",
      " 18  Mfr_Guarantee     1436 non-null   int64 \n",
      " 19  BOVAG_Guarantee   1436 non-null   int64 \n",
      " 20  Guarantee_Period  1436 non-null   int64 \n",
      " 21  ABS               1436 non-null   int64 \n",
      " 22  Airbag_1          1436 non-null   int64 \n",
      " 23  Airbag_2          1436 non-null   int64 \n",
      " 24  Airco             1436 non-null   int64 \n",
      " 25  Automatic_airco   1436 non-null   int64 \n",
      " 26  Boardcomputer     1436 non-null   int64 \n",
      " 27  CD_Player         1436 non-null   int64 \n",
      " 28  Central_Lock      1436 non-null   int64 \n",
      " 29  Powered_Windows   1436 non-null   int64 \n",
      " 30  Power_Steering    1436 non-null   int64 \n",
      " 31  Radio             1436 non-null   int64 \n",
      " 32  Mistlamps         1436 non-null   int64 \n",
      " 33  Sport_Model       1436 non-null   int64 \n",
      " 34  Backseat_Divider  1436 non-null   int64 \n",
      " 35  Metallic_Rim      1436 non-null   int64 \n",
      " 36  Radio_cassette    1436 non-null   int64 \n",
      " 37  Tow_Bar           1436 non-null   int64 \n",
      "dtypes: int64(35), object(3)\n",
      "memory usage: 426.4+ KB\n",
      "None\n",
      "==========================\n"
     ]
    }
   ],
   "source": [
    "# printing basic info about data\n",
    "print(data.columns)\n",
    "print(\"Data types---\")\n",
    "print(\"==========================\")\n",
    "print(data.dtypes)\n",
    "print(\"==========================\")\n",
    "print(\"Info---\")\n",
    "print(data.info())\n",
    "print(\"==========================\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "90003b37",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Price:\n",
      "10730.824512534818\n",
      "==========================\n",
      "Average Accumulated Kilometers on odometer:\n",
      "68533.25974930362\n",
      "==========================\n",
      "Average Cylinder Volume in cubic centimeters:\n",
      "1576.8558495821726\n",
      "==========================\n",
      "Average Quarterly road tax in EUROs:\n",
      "87.12256267409471\n",
      "==========================\n",
      "Average Weight in Kilograms:\n",
      "1072.4596100278552\n",
      "==========================\n"
     ]
    }
   ],
   "source": [
    "print(\"Average Price:\")\n",
    "print(data[\"Price\"].mean())\n",
    "print(\"==========================\")\n",
    "print(\"Average Accumulated Kilometers on odometer:\")\n",
    "print(data[\"KM\"].mean())\n",
    "print(\"==========================\")\n",
    "print(\"Average Cylinder Volume in cubic centimeters:\")\n",
    "print(data[\"cc\"].mean())\n",
    "print(\"==========================\")\n",
    "print(\"Average Quarterly road tax in EUROs:\")\n",
    "print(data[\"Quarterly_Tax\"].mean())\n",
    "print(\"==========================\")\n",
    "print(\"Average Weight in Kilograms:\")\n",
    "print(data[\"Weight\"].mean())\n",
    "print(\"==========================\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5f35d67a",
   "metadata": {},
   "outputs": [],
   "source": [
    "lb= LabelEncoder()\n",
    "data[\"Fuel_Type\"]=lb.fit_transform(data[\"Fuel_Type\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3db8ec29",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Id                                           Model  Price  Age_08_04  \\\n",
      "0   1   TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13500         23   \n",
      "1   2   TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13750         23   \n",
      "2   3  �TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13950         24   \n",
      "3   4   TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  14950         26   \n",
      "4   5     TOYOTA Corolla 2.0 D4D HATCHB SOL 2/3-Doors  13750         30   \n",
      "\n",
      "   Mfg_Month  Mfg_Year     KM  Fuel_Type  HP  Met_Color  ... Central_Lock  \\\n",
      "0         10      2002  46986          1  90          1  ...            1   \n",
      "1         10      2002  72937          1  90          1  ...            1   \n",
      "2          9      2002  41711          1  90          1  ...            0   \n",
      "3          7      2002  48000          1  90          0  ...            0   \n",
      "4          3      2002  38500          1  90          0  ...            1   \n",
      "\n",
      "   Powered_Windows  Power_Steering  Radio  Mistlamps  Sport_Model  \\\n",
      "0                1               1      0          0            0   \n",
      "1                0               1      0          0            0   \n",
      "2                0               1      0          0            0   \n",
      "3                0               1      0          0            0   \n",
      "4                1               1      0          1            0   \n",
      "\n",
      "   Backseat_Divider  Metallic_Rim  Radio_cassette  Tow_Bar  \n",
      "0                 1             0               0        0  \n",
      "1                 1             0               0        0  \n",
      "2                 1             0               0        0  \n",
      "3                 1             0               0        0  \n",
      "4                 1             0               0        0  \n",
      "\n",
      "[5 rows x 38 columns]\n",
      "Id                   int64\n",
      "Model               object\n",
      "Price                int64\n",
      "Age_08_04            int64\n",
      "Mfg_Month            int64\n",
      "Mfg_Year             int64\n",
      "KM                   int64\n",
      "Fuel_Type            int32\n",
      "HP                   int64\n",
      "Met_Color            int64\n",
      "Color               object\n",
      "Automatic            int64\n",
      "cc                   int64\n",
      "Doors                int64\n",
      "Cylinders            int64\n",
      "Gears                int64\n",
      "Quarterly_Tax        int64\n",
      "Weight               int64\n",
      "Mfr_Guarantee        int64\n",
      "BOVAG_Guarantee      int64\n",
      "Guarantee_Period     int64\n",
      "ABS                  int64\n",
      "Airbag_1             int64\n",
      "Airbag_2             int64\n",
      "Airco                int64\n",
      "Automatic_airco      int64\n",
      "Boardcomputer        int64\n",
      "CD_Player            int64\n",
      "Central_Lock         int64\n",
      "Powered_Windows      int64\n",
      "Power_Steering       int64\n",
      "Radio                int64\n",
      "Mistlamps            int64\n",
      "Sport_Model          int64\n",
      "Backseat_Divider     int64\n",
      "Metallic_Rim         int64\n",
      "Radio_cassette       int64\n",
      "Tow_Bar              int64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(data.head())\n",
    "print(data.dtypes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4838787",
   "metadata": {},
   "source": [
    "## Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "52bc7510",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# checking the outliers\n",
    "sns.boxplot(data=data.loc[:, ['Price', 'KM','Quarterly_Tax']],palette=\"tab10\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "32c29924",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x23c211986a0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fuel type wise price\n",
    "ax=sns.barplot(x=data[\"Fuel_Type\"],y=data[\"Price\"],data=data,palette=\"hot\")\n",
    "plt.title(\"Fuel type wise Price\")\n",
    "ax.legend( bbox_to_anchor=(1,1),labels=[\"Petrol\",\"CNG\",\"Diesel\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "40b064c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Fuel type wise Price percentages')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=data.groupby([\"Fuel_Type\"])[\"Price\"].sum().plot(kind=\"pie\",colors=['red','yellow','violet'],autopct='%.2f%%')\n",
    "ax.legend( bbox_to_anchor=(1,1),labels=[\"Petrol\",\"CNG\",\"Diesel\"])\n",
    "plt.title(\"Fuel type wise Price percentages\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fbaa579a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Accumulated Kilometers on odometer VS Price')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "sns.lineplot(x=\"KM\",y=\"Price\",data=data,hue=\"Fuel_Type\",palette='tab10')\n",
    "plt.title(\"Accumulated Kilometers on odometer VS Price\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1c5e654a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Quarterly road tax in EUROs VS Price')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "sns.lineplot(x=\"Quarterly_Tax\",y=\"Price\",data=data,hue=\"Fuel_Type\",palette='tab10')\n",
    "plt.title(\"Quarterly road tax in EUROs VS Price\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "be21523b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Weight in Kilograms VS Price')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "sns.lineplot(x=\"Weight\",y=\"Price\",data=data,hue=\"Fuel_Type\",palette='tab10')\n",
    "plt.title(\"Weight in Kilograms VS Price\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b9026138",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Cylinder Volume in cubic centimeters VS Price')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "sns.lineplot(x=\"cc\",y=\"Price\",data=data,hue=\"Fuel_Type\",palette='tab10')\n",
    "plt.title(\"Cylinder Volume in cubic centimeters VS Price\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "28ec3a33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(data[[\"KM\",\"cc\",\"Weight\",\"Price\",\"Quarterly_Tax\"]].corr(),annot=True,cmap=\"RdBu\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b2c162c",
   "metadata": {},
   "source": [
    "## Linear Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec1527d4",
   "metadata": {},
   "source": [
    "### Prediction model for predicting price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e4d559c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      KM    cc  Weight  Quarterly_Tax  Price\n",
      "0  46986  2000    1165            210  13500\n",
      "1  72937  2000    1165            210  13750\n",
      "2  41711  2000    1165            210  13950\n",
      "3  48000  2000    1165            210  14950\n",
      "4  38500  2000    1170            210  13750\n"
     ]
    }
   ],
   "source": [
    "# multiple linear regression--\n",
    "df=data[[\"KM\",\"cc\",\"Weight\",\"Quarterly_Tax\",\"Price\"]]\n",
    "print(df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e959a6ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1436, 5)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e5f5103a",
   "metadata": {},
   "outputs": [
    {
     "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>KM</th>\n",
       "      <th>cc</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Quarterly_Tax</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>637</th>\n",
       "      <td>121626</td>\n",
       "      <td>1300</td>\n",
       "      <td>1050</td>\n",
       "      <td>69</td>\n",
       "      <td>7995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>41000</td>\n",
       "      <td>1600</td>\n",
       "      <td>1075</td>\n",
       "      <td>85</td>\n",
       "      <td>13995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1174</th>\n",
       "      <td>94447</td>\n",
       "      <td>1600</td>\n",
       "      <td>1050</td>\n",
       "      <td>69</td>\n",
       "      <td>7250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>58798</td>\n",
       "      <td>1600</td>\n",
       "      <td>1075</td>\n",
       "      <td>85</td>\n",
       "      <td>10950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>41700</td>\n",
       "      <td>1400</td>\n",
       "      <td>1025</td>\n",
       "      <td>69</td>\n",
       "      <td>10750</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          KM    cc  Weight  Quarterly_Tax  Price\n",
       "637   121626  1300    1050             69   7995\n",
       "298    41000  1600    1075             85  13995\n",
       "1174   94447  1600    1050             69   7250\n",
       "240    58798  1600    1075             85  10950\n",
       "551    41700  1400    1025             69  10750"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# train test split\n",
    "training,testing=train_test_split(df,test_size=0.2)\n",
    "training.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9642e782",
   "metadata": {},
   "outputs": [
    {
     "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>KM</th>\n",
       "      <th>cc</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Quarterly_Tax</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>58530</td>\n",
       "      <td>1600</td>\n",
       "      <td>1075</td>\n",
       "      <td>85</td>\n",
       "      <td>11750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1414</th>\n",
       "      <td>42186</td>\n",
       "      <td>1600</td>\n",
       "      <td>1050</td>\n",
       "      <td>69</td>\n",
       "      <td>7500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>5459</td>\n",
       "      <td>1600</td>\n",
       "      <td>1130</td>\n",
       "      <td>85</td>\n",
       "      <td>19950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>711</th>\n",
       "      <td>91333</td>\n",
       "      <td>1600</td>\n",
       "      <td>1050</td>\n",
       "      <td>69</td>\n",
       "      <td>8250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>48052</td>\n",
       "      <td>1900</td>\n",
       "      <td>1105</td>\n",
       "      <td>185</td>\n",
       "      <td>13500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         KM    cc  Weight  Quarterly_Tax  Price\n",
       "496   58530  1600    1075             85  11750\n",
       "1414  42186  1600    1050             69   7500\n",
       "166    5459  1600    1130             85  19950\n",
       "711   91333  1600    1050             69   8250\n",
       "272   48052  1900    1105            185  13500"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0950efc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((1148, 5), (288, 5))"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training.shape,testing.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f4aa0113",
   "metadata": {},
   "outputs": [],
   "source": [
    "# defining\n",
    "x_train=training[[\"KM\",\"cc\",\"Weight\",\"Quarterly_Tax\"]]\n",
    "y_train=training[\"Price\"]\n",
    "x_test=testing[[\"KM\",\"cc\",\"Weight\",\"Quarterly_Tax\"]]\n",
    "y_test=testing[\"Price\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a5766f32",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LinearRegression()\n"
     ]
    }
   ],
   "source": [
    "model = LinearRegression()\n",
    "print(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f9952f5d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model training is completed\n",
      "LinearRegression()\n"
     ]
    }
   ],
   "source": [
    "model_train=model.fit(x_train,y_train)\n",
    "print(\"Model training is completed\")\n",
    "print(model_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c829de4e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.05535487 -0.03469673 34.56353547  4.68238424]\n",
      "-22910.157682621873\n"
     ]
    }
   ],
   "source": [
    "print(model.coef_)\n",
    "print(model.intercept_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "6567e1fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6264743463447623"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_train.score(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f82d1fc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='KM', ylabel='Price'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"KM\",y=\"Price\",data=training)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "f06cba82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='cc', ylabel='Price'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"cc\",y=\"Price\",data=training)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c3b7a34b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Weight', ylabel='Price'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"Weight\",y=\"Price\",data=training)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "fa04acb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Quarterly_Tax', ylabel='Price'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"Quarterly_Tax\",y=\"Price\",data=training)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "90701b4d",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([11348.2105812 , 11313.92396236, 16186.9430797 ,  8593.39840549,\n",
       "       13422.95432712,  9283.64945141,  9426.21529106, 10841.82336379,\n",
       "        9643.31476737, 10436.5159524 , 10613.07601487, 14951.55403414,\n",
       "        8997.23410398, 12937.50390253, 10058.47625589, 15251.24527399,\n",
       "        8314.79800408, 11174.28559494,  8392.29796647,  6629.13480214,\n",
       "       12217.66944791, 11493.94050016, 10517.9210017 ,  5049.08238048,\n",
       "        9760.89165211,  3829.9499819 ,  6183.66147825,  8697.52154164,\n",
       "        8216.40152756, 15092.41260101,  7873.1762552 , 10048.14643021,\n",
       "       13717.64864542, 10861.9577564 , 16016.56080481, 10199.63052716,\n",
       "        5636.89884456,  9169.25885353, 14905.6099193 , 10476.09468097,\n",
       "       13078.89936978,  8215.82287039,  9646.97070483,  5560.86325577,\n",
       "       12282.22207265, 11982.55622479, 11881.42455612, 11859.41233752,\n",
       "       10764.65980454,  9536.99897071, 12371.35517648,  8310.20355028,\n",
       "        6382.91321081,  6995.69093305,  9860.40313901, 12572.62546612,\n",
       "       14121.4341813 , 11791.95580309,  9847.35595146,  9516.66662196,\n",
       "        9726.03583515,  8498.96300557, 12572.16958658, 11149.37611724,\n",
       "       10824.00000836, 10594.83128991, 12106.79365304,  7310.46086514,\n",
       "       10625.10976631, 12395.50101494, 10208.34340992, 12892.38989906,\n",
       "       10647.73517726, 10545.78666779, 12563.09265835,  8436.02852154,\n",
       "       12092.67816243,  8942.96731841,  7860.83548308,  9214.09629429,\n",
       "       11619.92565684, 17416.12133889,  8603.91876945,  7883.91509903,\n",
       "        9005.59311183,  9215.97751327, 12944.86631121,  9305.48402544,\n",
       "       10791.61762386, 11772.06278355,  5522.96922351,  9547.55021585,\n",
       "        7779.7416637 , 10067.13336056,  8064.07548357, 11482.31346211,\n",
       "       10924.23423359, 13805.23354449,  9750.09409061,  8774.85228824,\n",
       "        5857.78823363,  8304.33908577,  9071.27695621, 11519.14661635,\n",
       "       10382.91342522, 10847.09183911, 11158.15537187, 10152.10307855,\n",
       "        9334.12338998, 11340.5153438 , 11822.41375351,  9718.92887831,\n",
       "        7311.21745035, 18026.15644919, 10195.20213795,  9116.17226821,\n",
       "       10750.4120701 , 11418.01306614,  9506.16694566,  8553.37956597,\n",
       "        8108.05073399,  5118.80078406,  9405.29199847, 12672.90785879,\n",
       "       14905.6099193 ,  6661.31457329,  8751.32583572, 12452.38292808,\n",
       "       10826.10622121,  7161.42697368, 11603.54061676, 13734.52196925,\n",
       "       16156.99609766,  6458.7843946 , 11161.16606869,  9536.75959156,\n",
       "        6250.06468568, 10369.90209232,  9255.35468655, 11135.26041502,\n",
       "       17180.25425854,  8384.16058969, 13024.29863819, 13597.00176577,\n",
       "        7600.90784251, 12755.16518838, 13627.59878104, 16488.2949655 ,\n",
       "       11056.93328085, 10782.15931265, 12256.14192561, 10376.43732921,\n",
       "        8230.84599616,  8469.79477766,  8840.74674668, 11115.42205081,\n",
       "        8198.5743214 ,  8457.19309775,  8913.68544119,  7726.15373339,\n",
       "        9609.23833937,  9320.37678892,  6272.095922  ,  9928.45082888,\n",
       "       10474.21261556,  7568.22693798, 16014.5126748 ,  9488.12147123,\n",
       "        6879.77784545, 11524.23905234, 11513.42668234, 15367.08217216,\n",
       "       10577.89115521, 15464.08473044, 12460.36579962, 11611.53367466,\n",
       "       14380.43747918, 12257.58030567, 15779.88423605,  7900.68596583,\n",
       "       11255.34574046, 11547.1559665 ,  7638.97276039,  9729.78137147,\n",
       "       15824.9222617 ,  8777.14337181,  8889.66016007, 10788.8498806 ,\n",
       "        9858.8135621 , 10246.01853897,  8939.48038513,  9276.08995722,\n",
       "        8426.83625112, 10133.37777041, 11771.06724242, 11812.33959127,\n",
       "       10537.70464587, 10857.76541804, 10871.27306318,  9160.30911345,\n",
       "        8895.3621344 ,  6638.3970243 , 10999.91798137, 11909.10198868,\n",
       "        7633.9363141 , 10486.72281508, 13189.60910006, 11546.49079698,\n",
       "       12565.63013015, 13923.87245602, 11037.63505588,  9410.40239414,\n",
       "       12563.02823988, 10559.49314024, 12279.43053689, 11279.93607517,\n",
       "       12122.2528985 ,  8600.818897  ,  8055.53756149,  9726.12564561,\n",
       "       11649.50690053,  7870.68907229,  7639.60995685, 11474.143111  ,\n",
       "        9942.1963719 , 10404.00132407,  8504.16887926, 10768.64514322,\n",
       "       14242.29214714, 10992.20190941, 10670.53436488, 11028.70272285,\n",
       "       29416.56379276, 13100.85505151, 10093.02557869, 11123.96802253,\n",
       "       12924.38773908, 15201.98166507,  9150.62222366, 12325.16880761,\n",
       "        9742.75427408, 11985.19963729, 11502.6844757 , 11199.47736446,\n",
       "       11168.52890058,  8915.86329867,  7787.30115789, 12602.84922248,\n",
       "        9516.00172875,  9532.60503709, 17362.92531349, 15090.52926594,\n",
       "        6674.41129579, 11809.68213453,  9763.26876012, 23006.37555976,\n",
       "       12574.23075721, 13988.65615509, 11364.04249585, 14333.0532914 ,\n",
       "        9869.21733716, 14159.70268836, 10629.11615117, 10159.74162672,\n",
       "        8115.24308044, 10726.13169565,  8528.9099876 ,  9689.22527305,\n",
       "        9756.20996575,  8943.9318283 ,  8549.79373975, 11493.32908027,\n",
       "       14279.03812273, 12768.17337008,  9738.8044261 ,  8837.68321136,\n",
       "       11812.3055589 ,  9725.79351642, 12312.42354149,  9106.28339991,\n",
       "       14860.64093424, 12047.34252788,  8966.5461862 , 13940.3421143 ,\n",
       "        6916.05808587, 11198.97471123, 10353.59457603,  9026.44308987])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_price=model_train.predict(x_test)\n",
    "pred_price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c0f9cae3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-37-60f1e46b7c8e>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  testing[\"pred_price\"]=pred_price\n"
     ]
    },
    {
     "data": {
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       "      <td>1050</td>\n",
       "      <td>69</td>\n",
       "      <td>8250</td>\n",
       "      <td>8593.398405</td>\n",
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       "      <th>272</th>\n",
       "      <td>48052</td>\n",
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       "      <td>13500</td>\n",
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       "      <td>9950</td>\n",
       "      <td>6916.058086</td>\n",
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       "      <th>968</th>\n",
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       "      <td>1600</td>\n",
       "      <td>1055</td>\n",
       "      <td>85</td>\n",
       "      <td>9950</td>\n",
       "      <td>11198.974711</td>\n",
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       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>73376</td>\n",
       "      <td>1600</td>\n",
       "      <td>1070</td>\n",
       "      <td>85</td>\n",
       "      <td>10950</td>\n",
       "      <td>10353.594576</td>\n",
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       "    <tr>\n",
       "      <th>855</th>\n",
       "      <td>64966</td>\n",
       "      <td>1300</td>\n",
       "      <td>1020</td>\n",
       "      <td>69</td>\n",
       "      <td>8950</td>\n",
       "      <td>9026.443090</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>288 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          KM    cc  Weight  Quarterly_Tax  Price    pred_price\n",
       "496    58530  1600    1075             85  11750  11348.210581\n",
       "1414   42186  1600    1050             69   7500  11313.923962\n",
       "166     5459  1600    1130             85  19950  16186.943080\n",
       "711    91333  1600    1050             69   8250   8593.398405\n",
       "272    48052  1900    1105            185  13500  13422.954327\n",
       "...      ...   ...     ...            ...    ...           ...\n",
       "169        1  1400    1065             19  17795  13940.342114\n",
       "394   126110  1600    1055             85   9950   6916.058086\n",
       "968    48738  1600    1055             85   9950  11198.974711\n",
       "803    73376  1600    1070             85  10950  10353.594576\n",
       "855    64966  1300    1020             69   8950   9026.443090\n",
       "\n",
       "[288 rows x 6 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing[\"pred_price\"]=pred_price\n",
    "testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "4987dc64",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-38-8a9376ad0a10>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  testing[\"Error\"]=testing[\"Price\"]-testing[\"pred_price\"]\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "      <th>cc</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Quarterly_Tax</th>\n",
       "      <th>Price</th>\n",
       "      <th>pred_price</th>\n",
       "      <th>Error</th>\n",
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       "      <td>19950</td>\n",
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       "      <td>3763.056920</td>\n",
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       "      <td>9950</td>\n",
       "      <td>6916.058086</td>\n",
       "      <td>3033.941914</td>\n",
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       "      <th>968</th>\n",
       "      <td>48738</td>\n",
       "      <td>1600</td>\n",
       "      <td>1055</td>\n",
       "      <td>85</td>\n",
       "      <td>9950</td>\n",
       "      <td>11198.974711</td>\n",
       "      <td>-1248.974711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>73376</td>\n",
       "      <td>1600</td>\n",
       "      <td>1070</td>\n",
       "      <td>85</td>\n",
       "      <td>10950</td>\n",
       "      <td>10353.594576</td>\n",
       "      <td>596.405424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>855</th>\n",
       "      <td>64966</td>\n",
       "      <td>1300</td>\n",
       "      <td>1020</td>\n",
       "      <td>69</td>\n",
       "      <td>8950</td>\n",
       "      <td>9026.443090</td>\n",
       "      <td>-76.443090</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>288 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          KM    cc  Weight  Quarterly_Tax  Price    pred_price        Error\n",
       "496    58530  1600    1075             85  11750  11348.210581   401.789419\n",
       "1414   42186  1600    1050             69   7500  11313.923962 -3813.923962\n",
       "166     5459  1600    1130             85  19950  16186.943080  3763.056920\n",
       "711    91333  1600    1050             69   8250   8593.398405  -343.398405\n",
       "272    48052  1900    1105            185  13500  13422.954327    77.045673\n",
       "...      ...   ...     ...            ...    ...           ...          ...\n",
       "169        1  1400    1065             19  17795  13940.342114  3854.657886\n",
       "394   126110  1600    1055             85   9950   6916.058086  3033.941914\n",
       "968    48738  1600    1055             85   9950  11198.974711 -1248.974711\n",
       "803    73376  1600    1070             85  10950  10353.594576   596.405424\n",
       "855    64966  1300    1020             69   8950   9026.443090   -76.443090\n",
       "\n",
       "[288 rows x 7 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing[\"Error\"]=testing[\"Price\"]-testing[\"pred_price\"]\n",
    "testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "e35e35fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7101742103305064"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mltpl_r2 = r2_score(testing['Price'],testing['pred_price'])\n",
    "mltpl_r2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "99732bd5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='KM', ylabel='Price'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"KM\",y=\"Price\",data=testing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "062bec2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='cc', ylabel='Price'>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"cc\",y=\"Price\",data=testing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "dcf6b103",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Weight', ylabel='Price'>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SlhuGwb7KWl7ZXs7+qrp4+ZXD3BTPzWXu2EEcPXq02wJGVwxBJSNBQwjRY3iCEWr93ZOy3DAMPiivYf2Ocj48Xh8vnzDCzdK5ecy6LDtpeo1068ohqGQkaAghul0wolHj656U5YZhsPPYeUp2lFN60hMvv2ZUJsVz8pieN7Bbg0V3DEElrU93V0AI0X9FG1KWe7ohZblhGPzjyDlKdpTzyWlvvHxKzgCK5+QxJSer24JFfAjKYcZp7fohqGQkaAghulxi6o+unrfQDYNth89Ssr2cI9UXUhNNz82ieG4ek0ZndWl9EikKuKwWXHZTtw5BJdMzayWE6LP8oSg1/gihLl5Cq+kGWz+pZv3OCo6dvRAsZo/JpnhOHleNTJ7LLp162hBUMhI0hBBdIhTVqPNHunwJraYbvPPxGdbvqKDivD9e/rnLB7FkTi7jh3dPsIjlgjLh7oFDUMlI0BBCpFV3LaGNajp/LT3Dr3dVUFUTiJdfO24wS2bnMm6YO8mz00dVwNnDh6CS6X01FkL0Gt2xhDai6fzl0Gl+vauCk3VBIPat/p/yh3DPnFwuH+JKfoM0MasKbrsZl92CpQckMuwoCRpCiE4XDGvU+Lt2CW04qvPWoVP8emcFZzyx83tUBa67cij3zMnlskHOLqtLo946BJWMBA0hRKeJNCyh9QYjXTZvEY7qbP7wJBt2VXDWGwZiweKGq4ZRNCuXnOyMLqrJBY1DUG67Gbu1Zxzp2lkkaAghLpmux45ZrevCJbTBiMYfDpxk0/uVnPPFgoVJVbjxqmEUzc5lVJajS+qRqK8MQSUjQUMIcUm8oQi1vgjhNJ/L3SgQ1vj9/hO8+kElNf4IEPuw/uLVwymclcvwAfYuqUej+BBUhhmnpW8MQSUjQUMI0SHBiEatP0Kgi07P84Wi/H7fCTZ9UEl9MAqAxaRw8zUjKJyZw9DMrg0WqgJOmwW3re8NQSUjQUMI0S5RTac2EMHTRafneYNRfru3itf3HMfTECysZpUvTxrBXTNzGOyypb8SCSwmhUFuB6MGZvTZIahkJGgIIVJiGEbDEtpIl5yeVx+I8Ns9x3l9bxW+UGwVlt2scuuUkdw5I4dspzXtdWikAHaLCZfDjMtqxnta65cBAyRoCCHaoChKl6b+qPNHeHV3Jb/bdwJ/OPZ6DouJ26aOZPH00WRldF2w6K9DUMlI0BBCtCoU1agLw+n6YNrnLc77wmz6oJI39p8gGIlNqjutJu6YNoo7po1mgMOS5hpcYDEpuO0WXDYz5n7ao2iNBA0hRDONqT/qAxHq/SGGpPG1znpD/Ob9Sv544CShaCxYuGxmvjJtFHdMG4Xb3jXB4uIhqO48Q6Mnk6AhhIgzDANvKNolqT+qPSE27Kpg84cn46+VaTezeMZobpsyCqetaz6eTKqC02rGZTdjt8gQVFs6/W8lEomwcuVKjh8/Tjgc5qGHHmL48OE8+OCDXHbZZQAUFhZy8803s2nTJjZu3IjZbOahhx7iuuuuIxgM8vjjj3Pu3DmcTidr1qwhOzubffv28dxzz2EymSgoKODhhx/u7KoL0a8FwxrnfWGClzhvsevoeTa+X8nJ+gAjMh3cPTOHWWOz44+fqg+yYVcFbx08FQ8WWQ4Ld87M4f9MHomji+YOZAiqYzo9aLzxxhtkZWXxwx/+kJqaGm6//Xa+8Y1v8LWvfY177703fl11dTUlJSW8/vrrhEIhioqKmDdvHhs2bCA/P5/ly5ezefNm1q1bx6pVq1i9ejVr164lJyeHZcuWcejQISZOnNjZ1Rei3+nM1B+7jp7nJ3/7FLOqkGk3c84X4id/+5R/YRyjsx38elcFfz50Or5rPNtp5a4Zo/ny5JFd8i2/cQiqMReUDEG1X6cHjZtuuomFCxfGfzaZTBw8eJBjx46xZcsW8vLyWLlyJQcOHGDq1KlYrVasViu5ubmUlZWxe/du7r//fgDmz5/PunXr8Hq9hMNhcnNzASgoKGD79u0SNIS4BOlI/bHx/UrMqoKjIQA4LCbqgxHW/LmMukCExpcZ5LJSODOXL10zHFsXBAsZguo8nR40nM5YJkmv18s3v/lNHnnkEcLhMIsXL+bqq6/m5z//OT/72c8YP348bre7yfO8Xi9erzde7nQ68Xg8eL1eXC5Xk2srKyvbrIuu65SWlnbyO+z9gsGgtEsL+ku7qKpKSFeoD0YJhtruXYTCYY4cOZLSvSvPe3BaFELhKBHNoC6o4YtceIVsh4kv5ruZl+vEYgpSVfFZx99IGxRFwWaOBQqH2SBgGFR30m7E/vK70pK0zDSdPHmSb3zjGxQVFfHlL3+Z+vp6MjNjp2PdcMMNPPvss8yYMQOf78KRiz6fD7fbjcvlipf7fD4yMzOblCWWt0VVVSZMmNDJ7673Ky0tlXZpQX9ol8TUH6meKnHkyBEuv/zylK7NyfZysj6AP6jhCUXj5VaTyvLPX8GNE4elfVNcVwxB9fXflWQBsdP/9s6ePcu9997L448/zqJFiwC47777OHDgAEB8WGnSpEns3r2bUCiEx+PhyJEj5OfnM23aNN577z0Atm7dyvTp03G5XFgsFioqKjAMg23btjFjxozOrroQfVZU0znrCXGyLoA/TbmiDp/xEtF1TteH4gHDrCoMcJhZfctVfGnSiLQGDJOqkGm3MCLLwYgsBy6bReYs0qDTexr/+Z//SX19PevWrWPdunUAPPHEE3zve9/DYrEwePBgnn32WVwuF8XFxRQVFWEYBo8++ig2m43CwkJWrFhBYWEhFouF559/HoBnnnmGxx57DE3TKCgoYPLkyZ1ddSH6HMMwqA9EqE1jyvKPT3ko2VHOP46ci5fZzCp2s8plg5wUzsptsnqqs8kqqK6lGEZXpBzrHnv37mXq1KndXY0ep693rTuqr7VLZ6Usb214qvRkPa9sL2fnsfPxsrxBGRTPyeOf8odgSmOK8O5eBdXXflculuz9yeY+IfqYdKcs/7CqjpId5XxQXhMvGzvEyZLZeczPH4yaxg9wWQXV/SRoCNFHpDtl+f7KWv5nezn7KmvjZeOGulg6N4+5lw9Ka7CQIaieQ4KGEL1cOlOWG4bBR2eCvPj+Pj48XhcvHz/czdK5ecwek522oaHuHoISLZOgIUQv5gtFqU1DynLDMHj/sxpe2V7ORyfr4+UTR2aydG4eM/IGpu1DXIagejYJGkL0QqGoRq0v0unLZw3DYPvRc5Rsr+Dj0554+aTRA1g6N4+pOVlpCxYyBNU7SNAQohfRdINaf5j6Tp630A2Dvx8+R8mOcg6f8cbLp+Vm8flcCzfPvqrzXiyBpCPvfVIOGp999hnl5eVceeWVDBs2TP5yhehChmHgDUap8Yc7dd5CNwy2fnKW9TvKOXr2QtaFGXkDWTo3j6tHDUg5hUh7yBBU75VS0Fi/fj1vv/02dXV13HbbbVRUVPDUU0+lu25CCCAQjlLji1xyyvJEmm7w7sfVrN9ZTvk5f7x8zthsiufkMWFE22l6OkKGoHq/lILG5s2b+fWvf83SpUv56le/yle+8pV010uIfi8c1an1h/GFOm/eQtMNtpSeZv3OCqpqAvHyeZcPonhuHvnD3Eme3TEKYDObcGfIEFRfkFLQaNw03viXbbV23cHuQvQ3jUeteoLRTkv9EdV03v4oFixO1gXj5fPzB1M8O4/Lh6aavjB1qgJOqwW33Yy9iw5WEumXUtC45ZZbuOeeezhx4gQPPPAA119/fbrrJUS/FNtv0XlHrUY0nT8fOsWvd1Zyqj4WLBRgwZVDWDInjzGDnZ3yOonMqoLLbsZtt6Q9o63oeikFjSVLljBnzhw+/fRTxo4dy5VXXpnueglxSd4tO8NLW49SWeMnZ2AGX58/lgXjh7b5WHcJhjVq/GECkc6ZtwhHdf508CQbdlVyxhMCYt/8Pz9+KEtm55E7KKNTXqeRAljNJjIbNuKpacw7JbpXSkFj06ZNHD58mJUrV3Lvvfdy6623ctttt6W5akJ0zLtlZ3jqjUNYTApZDgtnPEGeeuMQ/97weGuPDeuGunbmUasAoYjG5g9PsuH9Ss55w0AsWNx41XCKZucwemDnBovGISiX3YTDKiv4+4OU/pY3bNjAxo0bAXjppZdYsmSJBA3RY7209SgWk0JGw4dYhtWMPxzlpa1HAVp97KlrB3RZHTv7qNVAROMP+0/wm/crqfFHgNgw0Y0Th1E0K5eRWY5Lfo1EFpOCy2bGJUNQ/U5KQUNVVWw2GwAWixxsIi7oiUM9lTV+QpEox8760I3Yt+FBTgvhqI4BZDksTa53WExU1fiBrgkavlCUGl/4klOWA/jDUd7Yd4JNH1RRG4gFC4tJ4earR3D3rByGZdov+TUayUY8ASkGjS984QsUFRUxadIkDh06xOc///l010v0AsmGgbo1cOg61d7IhR8NqPZGGD1AJWeQizOeYLynAbFv6Z09bNOSzkz94Q1F+d3e47y2u4r6YOyUPKtZ5UvXjODumTkMcdsuvcINLGYzmXaLbMQTQIpB45//+Z+57rrrOHbsGLfddhvjx49Pd71EL5BsGKg7g8b5QOxDVGn8jwFGQ/l354/lqTcO4Q9HcVhMBCIaEc3g6/PHgnEuyV07rjNTf3iCEV7fc5zf7jmOt+FIVZtZ5dbJI7lzxmgGuToxWDRsxAu7zQzuxCAkerekQePVV19l8eLFPP/88/GuaFlZGW+++Sb/+q//2iUVFD1XZY0/yVBP9wlFdSwqaAYYBigKmJVY+YLxQ/l3YgGvqsbP6IQhtdLSzg0ahmHgbRiKutTUH3WBCK/vqeJ/9xzHF46tsLJbVG6bMorFM0YzMKNz9k61NAR1Ur/0YTTRdyQNGsOHDwcgLy8Pk0m6paKpnIEZ3TbUk4zTGutB2BImaKO6jrNhaGXB+KFp7wl11hLaWn+YTR9U8ft9J+L3yrCauH3qKBZNG82ADEsbd0iNqoDT1rART4agRBJJg8a1114LwJtvvsnLL7/cJRUSvcfXkw31dKP7C8bwk78dJqrrqEpsTkM3YuXp1llLaM/7wvzm/Ur+sP8EwWjsm77TZuIr00bzlWmjcNs7J1hILijRXinNabjdbv76178yZswYVDX2izVmTPr/AYqeLdlQT3f65vX5APxy2zF8YQ2n1cT9BWPi5enQWUtoqz0hfvN+JX/88CThhmDhtptZNG00t08dhct+6XshFMDWcCKerIIS7dXmb6DX66Wqqor/+Z//iZcpisIrr7yS1oqJ3qErhno64pvX56c1SCTyhiLU+iKXtIT2dH2QjbsqefPgyXgKkUy7mTtn5PB/pozEabv0YBEfgrJJLijRcUl/E9evX8/LL7+MyWTiX/7lX5g/f35X1UuIHi8Y0aj1RwhcwhLak3UBNuyq5K2Dp+KT5QMzLNw5I4dbJ4/E0Qkf7rIRT3SmpEHjj3/8I2+99RZer5d/+7d/SyloRCIRVq5cyfHjxwmHwzz00ENcccUVPPHEEyiKwrhx41i9ejWqqrJp0yY2btyI2WzmoYce4rrrriMYDPL4449z7tw5nE4na9asITs7m3379vHcc89hMpkoKCjg4Ycf7rRGEB336MY9vHHgFJpuYFIVbp00nB/fPa27q5VWnbGE9nhNgF/trOAvH52icTRrkNPKXTNzuGXSiEuejJZ05CJdkgYNq9WK1WolOzubSCSS7NK4N954g6ysLH74wx9SU1PD7bffzvjx43nkkUeYPXs2Tz31FFu2bGHKlCmUlJTw+uuvEwqFKCoqYt68eWzYsIH8/HyWL1/O5s2bWbduHatWrWL16tWsXbuWnJwcli1bxqFDh5g4cWKnNILomEc37uF/952M/6zpRsPPe/ps4PAEI5e0hLbivJ9f7axgS+npeLAY4rJROCuHm68ZgdV8aT0BGYIS6ZbyQKmR4leqm266iYULF8Z/NplMHDp0iFmzZgEwf/58/v73v6OqKlOnTo0HptzcXMrKyti9ezf3339//Np169bh9XoJh8Pk5uYCUFBQwPbt2yVodLM3DpxqtfzHd3dxZdIsGNGo8XV8Ce1n53ys31HBO2Vn4kNZwzJtFM7K5aaJwy85WJhVBbddhqBE+iUNGocPH+Zb3/oWhmHE/9zo+eefb/E5TmcsP7/X6+Wb3/wmjzzyCGvWrIl3j51OJx6PB6/Xi9vtbvI8r9fbpDzxWpfL1eTaysrKNt+cruuUlpa2eV1/8X6Vj9cO1XHKE2G4+wSLJg5g5uiOn6fQ2iohTTd6ZbsHg8Fm9VZUFW/YoD4QQevAJrequjB//NjDnhOBeLAYkmHi5iszmZOTgVkNUFl+rEP1VVUFh9WMy2bGqhr40rQJr6V26e/6c5skDRr/8R//Ef/z3Xen/tXx5MmTfOMb36CoqIgvf/nL/PCHP4w/5vP5yMzMxOVy4fP5mpS73e4m5cmuzcxs+wxjVVWZMGFCyvXuy94tO8Mv957CYjKRadPwaSZ+uddDbk7uJax+OtrqI72x3UtLS+P1Ngyj4UCkCFbdILud9/r0tIeSHRVsO3w2XjZ6oIMls3P5woRhmC7hvImuPhEvsV1ETF9vk2QBMWnQaBxSao+zZ89y77338tRTTzF37lwArrrqKnbu3Mns2bPZunUrc+bMYdKkSfzHf/wHoVCIcDjMkSNHyM/PZ9q0abz33ntMmjSJrVu3Mn36dFwuFxaLhYqKCnJycti2bZtMhLdTYp6oYDCCoxPyRGVYTfjDzYdrMnr5WHogHOW8L0Io2v6hqLJT9ZRsr2D70QspSXKzMyiek8uCK4deUrCQISjRE3T6qSn/+Z//SX19PevWrWPdunUAfOc73+G73/0uL7zwAmPHjmXhwoWYTCaKi4spKirCMAweffRRbDYbhYWFrFixgsLCQiwWS3wY7JlnnuGxxx5D0zQKCgqYPHlyZ1e9T7uUPFGtpT+fPDqLD4/X4g1d+HB12UxcMyqrs6vfJQzFRHV9CG+o/bu5Dx6vY/2OcnZ9VhMvGzPYSfGcXK4dN6TDwUJOxBM9jWKkOsPdC+3du5epU6d2dzV6hMJf7IjniQoGA9jtDqo9QfxhjUxHbLWNYRh4w1qTwPBu2Rkef20/nmCUqK5jVlXcdjM/XBQL2q091hM3/LVG1w3qAmH2lx4mNy+vXc/dX1VLyfZy9lTUxssuH+KkeE4eBeMGo3ZwqauigKuHnIjX14diOqKvt0my9yfnM/YTiXmiFMOg2hOk2htmqNuKSYGPT3kwiE2unvWGeOy1/fxo0WTWvFVGjT+CSVUwm1QMA2r8Eda8VcaKm8YTjGiENb0hv5NOsJPOuO4q3lCEGl+EiKYTiUZTeo5hGOyrrOWV7eXsr6qLl185zE3x3Fzmjh3U4X0RZlXBZTfjslkueUWVEOkgQaOfSMwTdfRMiEBUY6jbymCXnU9O1dO47kbXDQxFodYf4Qd/KuXYOT+qQvwbs6KAoRgcPevjB38qJRDRsahqrNyAQETnB38q7fE9jY7s5jYMg93lNZTsKOfD4/Xx8gkj3Cydm8esy7I7FCziQ1B2M06bDEGJnk2CRj/SmCeqtLSUB944GZ/jCDfkOmr8qFJVBUM3OHYu+XxHPKCoCQElhed1J003qPGH8bRjN7dhGOw8dp71O8r56KQnXn7NqEyWzMljRt7AjgULBZxWM267uduHoIRIlfym9hKdfRZ3S2dhQOyDLNGYQRkcrvah6Ea8N6EbcMXgjB4dHC5mGAbeYJQaf+q7uQ3D4B9HzlGyo5xPTnvj5VNyBlA8J48pOVkdChYyBCV6M/mN7QUaz+I+4wk2OYv73bIzHb7n1+ePJaIZ+MPR+AeXQewDTTcMdAPGDnbyxBcnkJVhQVFBMwwUFbIyLDzxxQmMHexsmMswMDCaPK8nCYSjnKwNUu0NpRQwdMNg6yfVLCvZzZO/PxQPGNNzs/jxXZN54c4pTM1tX++iMRfUEJeN0QMzyHbaJGCIXkl6Gr1AOs7iTpzjqPOHiWg6hhEbqlIVA5fVxIqbxrNg/FB+tGhyq2dmxFdPabHVUwMzLKy4qWecIR+O6tT5IykvodUNg3fKzlCyo5zPEnpRsy4bSPHcPCaOHNDuOjQOQblsZjLamd68s3uXQnQGCRo9SGsfEuk6i7txjqOlZbW2hCyrrZ2ZsWD8UH6YJKB0l8YltPXBaEoHImm6wTsfn+Hlrac55T0eL//c5YNYMieX8cPbzj5wMZMaS0futndsCKqxd2kxKU16l/8O3d6+on+ToNFDJPuQSPdZ3C9tPYrZpGBSFTRDaVheq6TUk+lphzB5QhFqfeH4QUbJRDWdLWVn+NXOCqpqAvHya8cNZsnsXMYNcyd5dnOxVVAqmXYLGTbzJe3+TkfvUojOIEGjh0j2IdFZZ3E39mSOnqlj7NC6eK/g0zMe6vwRVDUWMKK6wVlPmIjmSfme3T2E0p4ltBFN5y+HTvPrXRWcrAsCsQ/86aMcPPiFqxg7xJX8Bhe5lCGo1qSrdynEpZKg0UMk+5DojLO4E3sybqvSpCcTjupw0V4MXTHiZ1Sncs/uGkKJajq1gUhKS2jDUZ23Dp3i1zsrOOMJAbHkf9ddOZR75uSi1Z5qV8BoHIJy2c3YzJ2bbyvdvUshOkqCRg/R1ofEpQ4DJUtYaDEpBCKxuYDGZbUAVlPy4ZXuHEJJzELb1oqocFRn84cn2bCrgrPeMBALFtdPGMY9s3PJyY618ZHatl9XASwmNZYLyma5pCGoZDqrdylEZ5Og0UOk+0MiWU8mf1gmx8568QSjhDUdq0nFbbcwZnDyb93dNYTiD0Wp9UcItpGFNhjR+OOBk/zm/UrO+WLBwqQqLLxqGIWzcxmV5Uj5NRUFMiyxjXidNQSVTGf0LoVIBwkaPUS6PySS9WQaA9bwAeZ2BayuHkIJRTXq/BF8oeTzFoGwxu/3n+DVDyqp8ceOKTarCjddPZyiWbkMH2BP+TXTOQTVlp62yEAIkKDRo6TzQ+LihIX+cDQeGBaMH8qiqlp+ue0YvrCG02ri/oIxbdalq4ZQUp238IWi/H7fCTZ9UEl9MJZ80GJSuPmaERTOzGFoZmrBoquGoITojSRo9BMXJywcO9TeJP35a3uOM8RtI7fhw/+1PceZNDoraeBId+/IMGLHrNYFks9beINR/nfvcV7bU4WnIVhYzSq3TBrBXTNyGOK2pfR6JlWNrYKym8mwmjqcqVaIvkyCRj+SmLAwMVf+pUxop6t35AtFqfGFCWutr+CqD0T47Z7jvL63Cl/DQVB2s8qtU0Zy54wcsp3WlF7LpCo4bWaGZ9oY1o6hKyH6IwkaokftCUhl3qLOH+G1PVX8797j8eNmHRYTt00dyeLpo8nKaDtYNG7Ec9svDEFVG73rLBAhuoMEDUHOwIwWVk+Z46unkm3g66zNfbpuUBsI40mS+uO8L8yrH1Ty+/0nCEZiPRCn1cRtU0exaPpoBlwU+FqSjo14QvQn8q9GMHdsNrs+O99w2BKENZ1qb5iiWdlJN/ABnbK5r63UH+e8ITa+X8kfD5wk1LDh0GUz85Vpo7hj2ijc9raDhaQjF6JzSNDoR1pLI7L96HkG2M3UBiJEjFjgyHJY2H70PNuPnm91vgO4pM19baX+qPaE2LCrgs0fnowHlEy7mUXTR3Pb1FG42ugpNKYjdzvMOK1yIp4QnUGCRj/xbtkZHnttP95QLI15XWVN/BzwT8948ASjWEwXjm31BKN8esaD3WJqdb7DgA7NhbR1et6p+iAbdlXw1sFT8WCR5bBw54zR3DplZLODoy6mKuC0WXDbzNitXbu3Qoi+ToJGP/GDP5VS649gUhRUwNCJnwOeLPfUuKHupBv42rO5r63UHydqA/x6VwV/PnQ6Pq+R7bRy14zR3DJ5JA5L8gBgVhXcdjMuuwWLSYaghEgHCRr9ROJ53rquNDkH3GUztZp7qq0NfKlu7vOHotT4I4RaSP1RVePnVzsrePuj0zTGkkEuK4Uzc/jSNSOanO1xsdgqKFNsI54MQQmRdhI0RNLcU21t4Gtrc1+yJbTl53z8amcFfys7Ew8WQ902Cmfl8sWrhyedsO7qXFBCiJi0/Wvbv38/P/rRjygpKeHQoUM8+OCDXHbZZQAUFhZy8803s2nTJjZu3IjZbOahhx7iuuuuIxgM8vjjj3Pu3DmcTidr1qwhOzubffv28dxzz2EymSgoKODhhx9OV9XTqq0lquk6n2LsYCefnPYQ0TUMAxRdQwXyh7n4+vyxPP7afjTdwDAMND32v8YeQ7INfK09pukGtf4w9S3MWxw762P9jnLe/bg6HkiGZ9opmp3LwonDkg4tNW7Ec3dDLighRJqCxn/913/xxhtv4HDEsoh+9NFHfO1rX+Pee++NX1NdXU1JSQmvv/46oVCIoqIi5s2bx4YNG8jPz2f58uVs3ryZdevWsWrVKlavXs3atWvJyclh2bJlHDp0iIkTJ6aj+mnT1vkT6Tyf4otXD+fj0574B7hhgKHEyoHYh7dCLHWGQkpnarfEMAy8wSg1/nCzeYvDZ7ys31HO1k/PxstGZtlZMjuP6ycMxZwkWFhMCm67BZfNnPS6S9VTDpUSoqdKS9DIzc1l7dq1/Nu//RsABw8e5NixY2zZsoW8vDxWrlzJgQMHmDp1KlarFavVSm5uLmVlZezevZv7778fgPnz57Nu3Tq8Xi/hcJjc3FwACgoK2L59e5tBQ9d1SktL0/EWO+SFP5/A0KKoikooFIlNSGs6L7z1IcOMkW0+fin+evAE2Q4VX9ggohtYVAWnVeGvByv568FKHCadgZkXfh2C0fa9rqIoRA2VumA0toQ2oXtRXhvmj2X17DsVjJcNd5n50pVuZo7KwKT6KP/sWLN7qqqCw2rGbTNjVQ28evJDoS7V34/V8ss9FVhMYDcpVJ2r44nX9vLPswcxc7Qzra/dkwWDwR7176gn6M9tkpagsXDhQqqqquI/T5o0icWLF3P11Vfz85//nJ/97GeMHz8et/vCGcxOpxOv14vX642XO51OPB4PXq8Xl8vV5NrKyso266GqapMcS93t/BsnyXJmNEmEZzMMagIRJkyY0Objl/raw7NcKIpCMBjAbndgNNzbgEt63cR5i8R1U6Un6ynZUc6Oo+fjZXmDMlgyO48FVw5pNXusooDLasFlN+FoY3ltZ1rx5y04Hbb4ajAH4A9H+dOxKEtv6Dm/R13t4lxlou+3SbKA2CX/Im+44QYyMzPjf3722WeZMWMGPp8vfo3P58PtduNyueLlPp+PzMzMJmWJ5b1NW+dPpPN8irbu3ZHXbW3e4uDxOl7ZXs4H5TXxsrGDnRTPzePacYPjS3sv1nh2hdvePbu2T3ujDMlsmrdKzuUWoqku+Zd53333ceDAAYD4sNKkSZPYvXs3oVAIj8fDkSNHyM/PZ9q0abz33nsAbN26lenTp+NyubBYLFRUVGAYBtu2bWPGjBldUfVO9fX5Y4losbMsjIvOtEjl8XS9dntfN5ayPMzxGj91gQsBY19lLf+6aT/f3LgvHjCuGOrimVsn8oul0/mn/CHNAkZs17bKEJeN0QMzGOSydVuaj2EuM4FI0yXBci63EE11SU/j6aef5tlnn8VisTB48GCeffZZXC4XxcXFFBUVYRgGjz76KDabjcLCQlasWEFhYSEWi4Xnn38egGeeeYbHHnsMTdMoKChg8uTJXVH1TtXW8tVkjydO0GIYnPdFCGl6/MCkb16fn/JrN56nMXdsdvyeCnCiNkhYM5IewuQNRaj1ReIpyw3DYG9FLa/sKOdAVV38uiuHu/l/5uYxe0x2i+dS9MQls4smDuCXez1yLrcQSSiGkewstN5t7969TJ06tburcckSV1XVB8JUe2NHmFpUQFHQDfiXz1/RZuBoVFpaymllUPyeUU3neG1sknpUlh2zSSWiGfz7rRPjgePiPFGGYfBBeQ2vbC/n0In6+L0njsxk6dw8ZuQNbDFYNC6ZddnM2NvY4d3VGttFzuVuqq+P33dEX2+TZO+vZ3zFE0klHpJ07GxsbkcBNANsJpWorvPLbcdSDhoX3/NotTc2KW3AWW+YsUNc+MNRfrntGJ+7YjB1gQjeUGwYyjAMdhw9T8mOcspOeeL3mzR6AEvn5DE1N6vFYNGY4sNtt6R1yeylknO5hUhOgkYvkHhIUuPWh9i3/djKJQWoD0YpWPO3lPcWVNb4MSlwtNqLL6yhKmBSFMKagarAMLeNUETjZF0ATTfQDYO/Hz5HyY5yDp/xxu8zNTeLpXPymJyT1eLrWE0qAxwWnDZJ8SFEXyBBoxdIXPmk0HTjXeL+uVN1Ac56Qjz+2n5+uGhy0sDhtpn59Eysh6E25JuKGAZDXVYGuWxUe4JYVJWIprP1k7Os31HO0bMXVrDNyBtI8Zw8rhk9oNm9FcBuuZCSXM7aFqLvkKDRCyQmDUxMKHgxs0nFMKDGH2HNW2VJg0Z8KsuI9TCsFpWBTiuGpnOs2ksgorEgfyj3/c8HlJ+7sOR09phsls7NY8KI5kue4ynJ7T1vvkII0TkkaHSxxFVQbps5lnYjrJEzMIO5Y7PZfvR8sxQWC8YPxbdpL+f80aT3VlBiQUUxmvQKWuINa4zKslMfjOKymTCpCmc9IXxhnZyBGWg6bPzgwgbKeZcPonhuHvnD3M3u1VpKcknJIUTfI0GjCyWugjIp8GnD3MCoLDvHznrZ9dl5hrqtDHLamuSdWvW/B9oMGO2Vl51BMKIxZrCLWn8YXyiKxWzCokFFwma2+eMGs2ROHlcMdTV5flspydOZR0sI0X0kaHShZCuWIDa8Ux+IMthlb3J0alVdKKX7G4aBYcTmOa4Y3PqGNFVVua9gDP+/P3/MmfogIU3nnC8SP/hIARZcOYQlc/IYM7hpziVFAac1tr8iWYqPxPcK7T8KVgjRM0nQSFFnDLUkroIKa3o891LjRjlVufBnSC2FReLEuGYYmFSFLJuFJ77Y8hprTyhCtV9j5HAHVw5z8+bBC+dvK8AXJgzlntm55A1qGizam+Ij8b225/0IIXo2CRop6KyhlsRVUFaTGksdbsSWpQLxA5AaNaawqKwJtHrPDKsJmzl2rwEOS6sb0oJhjRp/mFp/mD9+dJ63Nx/nXEIP54arhnHP7NwmKTMUwGJSY0NQNkurCQbbeq8Xvx8hRO8lQSMFnTXUkrgKarDLGt+FPdxlIxTVqfaGyXTEJscTU1hsP3qu1XsOH2Bvtns7UTiqU+ePUO0N8sb+E/zm/Upq/LEd5SZV4aaJwymclcPILEf8OYoCjsYUH1ZTh5bMtnVMrBCid5KgkUTjkNSuz85jN6sMdtnIbBhyiWo6eypq2rWh7uLcUuOGujAMA184NiFdNCu2euriFBYWVSGit7zO9rNzfm6dNLzZa+u6QV0gzKn6IL/dc5xNH1RRF4gFC7MKN18zkrtn5TA80x5/TrIUH+0dnmsrz5YQoneSoNGKxCEpm0khrOmcqIsNEykKHK8NYu7AcFVimorGD2JvODbOP2l0VoupQJIlB1MVeOPAKcYM/iT+XE8wQlWNn1c/qOK13VXUB2MrrywmhS9dM4K5w3RmXj0u9l5oewiqo8NzkpJDiL5HgkYrEoekhmbaOVEbxMDgrDcUS6uhGxiqwsenPbET9oCvr9/NtNyBSb9RNwaKT894qPWHURUFAzjrDfHYa/v5UQs7uS0mpdnRqY3Maiz31Pqd5Sybfznl5338amcFv91zHG8oFixsZpVbJ4/kzhmjGeSyceTIkXiWWVcKQ1AdHZ6TfRpC9D0SNFqRuPrHbbcwMgvO1AcJRnUUDFBi8wWJH+UmxWjx3O/EzXzV3hADHBbq/WGiOjT2I6KaQTgS5qFf7WaQy9bkQzYQaf2YU7OqkO20Agrf3fwR/7v3OL5w7EwIu0XltimjWDxjNAMzYocLmVSFgS4bIwY4Ut613ZGVUO+WneHx1/bjCUaJ6nrK6U2EED2bBI1WXLz6x22PDd0MddvZX1WLPxxLFJjIoOm3cKDJsM7hM16iuoHTaiasN3+uAQQierMhoJYoCmQ5LGRlWDlVFyAQ0Vm/swKIrai6feooFk0bzYCM2Ie9xaTgtltw2cwEqmlXmo+OrIRa81YZNf4IJlVpV3oTIUTP1nNzVHezZKfZRaItf/NvTOfU+C08cVhHURQ0I5ZB9qw3+WY9RVHQdIMz9UG+vn53s8fdNjMjBtgJRnSOnfXFeyJOm4mlc/LY8MBs7isYQ1aGBYfFxJDM2Kl4WRnWhg/w9h2h0pETBY+e9aEqoCoKCgqqEkuM2FZ6EyFEzyZBoxULxg/l32+dyFC3nbpAhKFue3xZq6rG0oC09tF7YX+FH0fCN/rE/RjJFrF6ghFO1AbRjVhK8kZ2i8rwTDuaYXCiNhg/mtSsKgzPtJNhNfFhVR2HT3tx2y2MGOBgRJYDt81ySZlmk7WFEKJ/keGpJA5U1XLoRB2+sEZdIMKBqloWjB/KEKelxdQeBnDweB2ZDjNPfukqXtp6tMmwzhC3jaqaAGaTgqEbRFuIOhYVqj0hoppOY3/GYlLItFsIRjVO1QebXD8ww4JhGNjNKoNcdqwWlZKd5Qxx25h/ZfIP9fZMVLd3JdSYQRkcrvah6EY8M29b6U2EED2f9DRa8eJfP+HHf/2U+mAUTTeoD0b58V8/5cW/foLbYaXhpNUW1QWirPrdh3xyup6qmgBnvUGMhhQfAzMsXJadQSuLoYjo4Atr6MQmrbMzrNjMJs75wvhCWvPrNR27xcTQTDs2i4lAWMcTjPLz944mfX+Ny2jPeIJN5lDeLTvTvoZqxRNfnEBWhgVFjaU3UVTIymg9vYkQoneQoNGKn71zuNnwk9FQ7glFycl2kJEw9KRwYc8DwIm6ICMGOBiYYeG8L8Kp+iBD3XaK5+Qx0Gmj9fVQsWA0wGHBblE57w/Hl84mclhMjBhgZ4jLSiSq8dHJOjwNAS6VHE8Xz7dkWM1YTEp8Av9SLRg/lKVz8rCaVPSGVClL5+TJkJYQvZwMT7UipLXcFQhpBvWBCE6bibFDXHx4vA64ML/RmHBQN2IT2naLCYUInmCUGl+Ikh3l8V3lLXHaTGAQ3719MbfNzIAMC4YBtf4w9cR6G4m1TSXHU7oTCr5bdobX9hxniNtGbkMakdf2HGfS6CwJHEL0YtLT6IAMq4kznjBnvcEmQ1SJo1WqEpvQrjjvJxjVCUV1yk57OesNx1OQN7mnxYTDasIX0uL7LBLvm5VhITc7gwybibPeEMdrA/jCGkPcNnQjNpSV6somiC2jbZxIb9SZCQXT3ZMRQnQPCRqtsJpaX200xB0bFvKFNJSEz/+mG/3geG2g2dyFARxP+DbvMKs4LCb8EY1AQ7BozORhURWGuGzkZGdgVhVO1gU4XR8imLDZL3GepD0rmzqyjLY9Ll45BpIaXYi+IG1BY//+/RQXFwNQXl5OYWEhRUVFrF69Gl2Pfeht2rSJO+64gzvvvJN33nkHgGAwyPLlyykqKuKBBx7g/PnzAOzbt4/Fixdz991389Of/jRd1Y57+LorWiwf4ortrLaZVUJRHUVVMKsXehmNcxs6xM+puFhEB7tZxW5RCUT1Zt/4rabY0trhWXbCmk5VjZ+z3nCL96v2hCi4YhADnTYMoMYXYs1bZRSs+RuFv9jR6sR2upfRprsnI4ToHmmZ0/iv//ov3njjDRyOWLrt73//+zzyyCPMnj2bp556ii1btjBlyhRKSkp4/fXXCYVCFBUVMW/ePDZs2EB+fj7Lly9n8+bNrFu3jlWrVrF69WrWrl1LTk4Oy5Yt49ChQ0ycODEd1QdiyQMdZoXARetiM6xm6gMRKmua9iJMCowemEGmw0K1J4g/rMUTBSaymWIRJtjCBkG3zcSADCt6w2otb33bR7w6bSbeOHCKIS4rNrPK4erY5rlRWfZWU5ocPVPH2KF1fH3+WDYsm9O+hkmRpEYXom9KS08jNzeXtWvXxn8+dOgQs2bNAmD+/Pn84x//4MCBA0ydOhWr1Yrb7SY3N5eysjJ2797NtddeG792+/bteL1ewuEwubm5KIpCQUEB27dvT0fV49a8VUZEj/UoEoeqTtUHWxx20gw4URfAH45iNZt48e6pTR63mdVY70SLzW80UoBMu5nc7AwcVjPVnhAn6oItrphqSX0g2jB/EuWsN4xJUTCpCme94SbzCIlLbN1WpdOX2F5MNgQK0TelpaexcOFCqqqq4j8bhhHfkex0OvF4PHi9Xtxud/wap9OJ1+ttUp54rcvlanJtZWVlm/XQdZ3S0tKk17xf5eO1Q3Wc9kYZ5jKzaOIAZo52cviMp6HyDUtp1diwUqiVFCIQG45ymjQmjbTxwlsfArFgAc2fpwADHGYyHVYCYY2TdYFWh7OSCUU1DB38mhafU7GoENIhGAygGAZHz4R44a0PMbQoqhJbAqvqEQxN54W3PmSYMbLdr9uSltryqWsHAANiFxjnKC1t/UCp7hYMBtv8femPpF2a689t0iVLblX1QofG5/ORmZmJy+XC5/M1KXe73U3Kk12bmZmZ0utOmND6ZrJ3y87wy72nsJhMDMm04oto/HKvh9ycXFT1MwzDiNc9tplPR1GUpIHjX2+6hid/fxCTomBtmPdI1LgSym234A9HOVEbaEgX0ubbaUYBTIpCCAOF2AS6biTMmdgd+MNRxg61x5bYOjNQFIVgMIDd7sBmGNQEIknbKFXJ2rK39C5KS0s7pS36GmmX5vp6myQLiF2yeuqqq65i586dAGzdupUZM2YwadIkdu/eTSgUwuPxcOTIEfLz85k2bRrvvfde/Nrp06fjcrmwWCxUVFRgGAbbtm1jxowZl1yvZMtCxwyK7drWdQPDiJ2foRux9BjJvPD2J9T6I3x2PkA4IWCoCmRnWMjJzkBVFI7XBjjrDcfPCU+yWKtVjZlxIbaKKvEeF6+IkiW2QojO0CU9jRUrVvDkk0/ywgsvMHbsWBYuXIjJZKK4uJiioiIMw+DRRx/FZrNRWFjIihUrKCwsxGKx8PzzzwPwzDPP8Nhjj6FpGgUFBUyePPmS61VZ46e6PthsI9+Rah8ZVhNmFVBA02MpQLJssTQYX/3v95vdy2ZW0Q2DAw2b/RqpSiw/lNNmwRuKcrw20Gyfhg5MGObmk9Me2jtCpSgKA+wmPKFovLdiMSlEDRjqtjfJJ9U4Ma2ksMS2vQcopXuzoBCiZ1CM9ubJ7kV++7cdvHqYVj/wrnryT/iTHHAEMHqADUVVm5xxfdkTm+OPO8wqUcNoNh9hUmGgw0qGzYwnGKEuEGkyBNW4h0HTY0NeLy2Zzr/8Zi/1gWjS410TKcD44W4+PePFpCrxxICabjBuqIs/PTK/yfVNV08NaLVdEo93TVz5lGwiu/AXO5qdueEPRxnqtqdthVZn6+tDDh0l7dJcX2+TZO+vT6cRMSkKZzyBVs+zbitgAFR7w3z83M3Nyh1WlahmELhozsKkQrbThsNioi4QobLGT0thORDR4vMQ44Y6WfNWGb6Q1uI8SKvvr2EXOHBhnKrxxxZetDFTbVu/8B053lWW2ArRP/TpHeEhzeBUXZCIpnV4bD1x6ErTDf6w/zgWk0IgrDfpXZjUWOrzUVkZhKM6lTV+6gKRFgNGI4PYUt2brxnB0bM+NN1IOWA03sEb1siwKIQ0PZauRNPJsCjNUpG0R0d2cy8YP5RF00ZR7QlRespDtSfEommjes0kuBAiNX26p6EAUd3grCdMRPN0+D5RTeeN/Sf46d8ONzt5TlUg22klw2qmLhDhvC+EluLnfmNP480PTxK56Lzx1J6vgK5TH2r6gvUhnUx7e4JPUx053lUSFArRP/TpoAGx40Z1xWiykqlRhkVNOkRlURWcNhOff/49Ks43/5adlWEh0x6b4K6q8aMbsT0SqXzHT5zTOHbOH4sg7YwaFpPK+UBsE6DS+J/YYqx4eUfMHZvNi3/7lKjemO5dIdNh4ckvXdXqczoypCWE6H36fNDQG2afG3d1J64KcrQSNGxmBZvZhC+sURuIUtvwARw78xqcNgsDHBYCYY0TtYHYstnG1+tgPTuyHEE3NCKaEgtURuweigJmJfkmxGTeLTvDKzvKY/ciFoDCmkGkje6TrJ4Son/o03MaBmA2KQxyWhk3LLPZaXXn/E2/jWdYVAbYzUR14if2qQo4rSZUIMthIS87A6tZ5WRdgGpvqEnAgFiyQZPSkGMqad2M+Ka+sYOdqGr7N2qEtVjdUGJBzm4xYTPHfnZaTW3foAUvbT2KNxRFUWKrsRoTMAbCyeeFJEGhEP1Dnw4aNpPC8AF2rGYTX58/ttkGtEYuq4ksh4VgVKcuIVjceNUwXv7qTCwmhdxsB267hWpvmGpPqNWUH5cNcsbu3UYMiGo6CrE9HCtuGk+Gpf1/FboBXxg/hIhmEIhoBCMaYU1DN+D+gjHtute7ZWco/MUOdn12nmBEJ6obsd5Pw/sIawafnml9XijdqdaFED1Dnx6e0gyjyQa3Vb8/GB9CUZVY7idFUagPRNAvWm30P1+bxeiBDhxWM1kZFs77wkRSmKzwhKKMyrJz1hsmlOS6EQMcTfZ+XD0qi7JTddQFou1KKbK7oo4sh5n6YOx5ugG3TR7ON6/PT/keifsy7GY1vvLKiP8npqV5oUYLxg/l34n1VKpq/E3emxCi7+jTQWPMQBsbll3INpszMIPzvhDZGVaqvSHqg9EW5xIsJoWxQ1xkZVhw2sw4LGb84WB8A10yjSuPEo+Cbcn/u+LzTX5u3OeQ7bRRec5HOMUpCYtJISfbGf/ZH45yqj6c2pMbJPbAnFZTq8t129oH2rgPRAjRd/Xp4amLffVzefhCGrvKazhc7WsWMBqXz44Y4GBklh2nLRZTV9w0noEZltgS3jYmhBOHadojcZ9DKgGjcVVTZ5yOl7gvI9n+DqWtiCmE6PP6RdA4Ux/k+2+W8thrB6hqIfcTQKbDzOiBGShAVY2/yQfkgvFD+eGiyUzNHciIAY6kr5V4jkR7JO5zSHTxx7RZjWWwHeyycvlgZ6dMPidOYoeTBMVkR+AKIfqHPj08pekG//6HQ/zmg0p8odiHot2s8uXJI7lrZg6L/nM7DouJQS4rEU1PeqZF4tBLYu6pZNe2dV2ii/c5NGqci76QJSSWcr14Th6TRmd1SuqOxBQgFlVpsQ0sKowbljwdfXuSHLY3IaIQomfo0z2NYzVhXv77Z/hCGg6Libtn5vDrB2bz0ILLyXZaGZ5pZ5DLyjlvmNP1F1ZEddb36YxWlr22VJ44RHTx6tvGj3AFmDDczRC3jdf2HAfolNPxEntHplaW/jospqTB6OLlzMlOBmzPtUKInqVP9zR0I7aP4fZpo/jKtNEMaFg5ZTEpZGVY8YejLZ7j3RarSSHcwrfxi4dvHpw/lv/Y8mmT1VCqEiu/WGLqjkFOK9Xe5pPZQ922+FkVjbutNyyb0ynf0Bt7R4W/2MFn57zU+CLxDYIWk8KogRlJX6c9O8Jl97gQvVefDhrD3WY2PDAblz0WLBQFMu0WsjKsmFSl1YDR1orXTIeFsy18qGdetCO6cdnrL7cdwxfWcFpN3F8wpsXlsIlDRK3VIHH1Urp2W1fW+BnktDHYdWFOxjAM6gKRNp+X6o5w2T0uRO/Vp4OG22bC3RAwGvdb2BNWGzWeP3GxthYJDXZaqfGFaTh0L554cLDT2uzab16fn9KeicR9DkerLyRFTJzPOOsLM6xhIj5du607kqywvc/r6GsIIbpfn57TALCaTQzJtDF8gL1JwADIdrQcM1srbxRLsRGbkLZbVKxmNV52KRaMH8qGZXMuzGE05PBovKtuND/GtbN1dGd3e54nu8eF6L36dE9DAUYMsLea12lopoPzfk+TwSCloTwZTyhKdoaFsw29jcZehjfUfLjrxb9+ktLwVJN6X9wDSuhu1AUiad1t3dGd3e15nuweF6L36tNBA0iaCNATipKb7eCsN0xY07GaYvsfWvrwT+S2mfm0LojFpMY/4M/7I4wb2nSPxYt//YSf/O0wqhLbXxGIaPzkb4cBkgaOUQPsVNUGmw2djc6yN9tJng4d3dndnufJ7nEheqc+PzyVTM7ADMwmlbFDXIwfnsnYIS7MJrXNsfUmR6w2/o/maTZ+ue1YQ8BQURW14f9j5cl897ZryLSZ4ktvVQUybSa+e9s1HXiXQgjRefp10Ojo2Lo3rDEqy47ZpKAZBmaTwqgse7MUHL6w1mzPhaokT9UBsW/hLxZOY/aYQeQMdDB7zCBeLJwm38yFEN2uzw9PJdPRsfXEpISN/OFos9QhTmtsl3Zi4GjcO5JK3SRICCF6mn4dNKBjH86JeyqSpe+4v2AMP/nbYaK6jqoQT13e3rMuhBCip+jSoHHbbbfhdrsBGD16NA8++CBPPPEEiqIwbtw4Vq9ejaqqbNq0iY0bN2I2m3nooYe47rrrCAaDPP7445w7dw6n08maNWvIzs7uyurHpdpDac/mPiGE6A26LGiEQrEjiUpKSuJlDz74II888gizZ8/mqaeeYsuWLUyZMoWSkhJef/11QqEQRUVFzJs3jw0bNpCfn8/y5cvZvHkz69atY9WqVV1V/WZS7aGkurlPCCF6gy6bCC8rKyMQCHDvvfeydOlS9u3bx6FDh5g1axYA8+fP5x//+AcHDhxg6tSpWK1W3G43ubm5lJWVsXv3bq699tr4tdu3b++qqgshhGjQZT0Nu93Offfdx+LFi/nss8944IEHMAwjvova6XTi8Xjwer3xIazGcq/X26S88dq26LpOaWlpet5QLxYMBqVdWiDt0jJpl+b6c5t0WdAYM2YMeXl5KIrCmDFjyMrK4tChQ/HHfT4fmZmZuFwufD5fk3K3292kvPHatqiqyoQJEzr/zfRypaWl0i4tkHZpmbRLc329TZIFxC4bnnrttdf4wQ9+AMDp06fxer3MmzePnTt3ArB161ZmzJjBpEmT2L17N6FQCI/Hw5EjR8jPz2fatGm899578WunT5/eVVUXQgjRoMt6GosWLeLb3/42hYWFKIrC9773PQYOHMiTTz7JCy+8wNixY1m4cCEmk4ni4mKKioowDINHH30Um81GYWEhK1asoLCwEIvFwvPPP99VVRdCCNFAMS7OfdGH7Nu3D5vN1vaFQggh4kKhEFOmTGnxsT4dNIQQQnSufp17SgghRPtI0BBCCJEyCRpCCCFSJkFDCCFEyiRoCCGESJkEDSGEECnrtUFj//79FBcXA1BeXk5hYSFFRUWsXr0aXdcB2LRpE3fccQd33nkn77zzDhDLGbN8+XKKiop44IEHOH/+fLe9h3RIbBeAt99+m29961vxn/ft28fixYu5++67+elPfxov/+lPf8qiRYu4++67OXDgQJfWuSsktktpaSlFRUUUFxdz3333cfbsWaD//b4ktsnhw4cpLCzk7rvv5umnn0bTYqdL9rc2geb/hgD+8Ic/cNddd8V/7o/tEmf0Qr/4xS+MW265xVi8eLFhGIbx9a9/3dixY4dhGIbx5JNPGn/5y1+MM2fOGLfccosRCoWM+vr6+J9ffvll48UXXzQMwzD++Mc/Gs8++2y3vY/OdnG7PPvss8bChQuNRx55JH7NrbfeapSXlxu6rhv333+/cfDgQePgwYNGcXGxoeu6cfz4ceOOO+7orreQFhe3yz333GN89NFHhmEYxoYNG4zvfe97/e735eI2eeihh4xdu3YZhmEYK1askH9DDe1iGIbx0UcfGUuXLo2X9cd2SdQrexq5ubmsXbs2/rOkWI+5uF2mTZvG008/Hf/Z6/USDofJzc1FURQKCgrYvn07u3fvpqCgAEVRGDlyJJqm9alvSRe3ywsvvBBPNqdpGjabrd/9vlzcJmvXrmXmzJmEw2Gqq6sZNGhQv2sTaN4uNTU1/OhHP2LlypXxsv7YLol6ZdBYuHAhZvOFtFlGmlOs9xYXt8vNN98cbxeIBQ2X68K55olt1VJ5X3FxuwwdGjs8a8+ePaxfv56vfvWr/e735eI2MZlMHD9+nFtuuYWamhrGjBnT79oEmraLpml85zvfYeXKlTidzvg1/bFdEvWJM8JV9ULsS0eK9b6ipTbJzMzEYrG02FZ92ZtvvsnPf/5zfvGLX5CdnS2/L8CoUaP4y1/+wquvvsoPfvADbrzxxn7dJocOHaK8vJynn36aUCjE4cOHee6555gzZ06/bpde2dO42FVXXSUp1lPgcrmwWCxUVFRgGAbbtm1jxowZTJs2jW3btqHrOidOnEDX9W47f70r/P73v2f9+vWUlJSQk5MD0O9/Xx588EE+++wzIPYtWVXVft8mkyZNYvPmzZSUlPDCCy9wxRVX8J3vfKfft0uf6GmsWLFCUqyn6JlnnuGxxx5D0zQKCgqYPHkyADNmzOCuu+5C13Weeuqpbq5l+miaxnPPPceIESNYvnw5ADNnzuSb3/xmv/59WbZsGU888QQWiwWHw8F3v/tdhgwZ0q/bpDX9vV0ky60QQoiU9YnhKSGEEF1DgoYQQoiUSdAQQgiRMgkaQgghUiZBQwghRMokaAjRQUuXLo0ndwyHw0yfPp3/+3//b/zxJUuWUFZW1ux5v/3tb9myZUur933iiSfYunVrs/Lf/OY3RCKRTqi5EB0nQUOIDiooKOCDDz4AiOfvevfddwEIhUKcPHmS8ePHN3veHXfcwRe+8IV2v95LL70Uz+AsRHeRoCFEB33uc5+LB4333nuPxYsX4/F48Hg87N27l1mzZvGnP/2Ju+66i8LCQn70ox8BseSAGzZswDAMnn76aRYtWsSDDz7Il7/8ZaqqqoBYr2Lp0qXccccdHDhwgFdffZXq6moeffTRbnu/QoAEDSE67KqrruLo0aMYhsH777/PrFmzmDt3Lv/4xz/YtWsX1157LWvXruW///u/2bBhA6dPn+bvf/97/PlbtmyhtraW1157je9973ucPHky/tjEiRN55ZVXWLJkCb/97W9ZvHgxQ4YM4cc//nF3vFUh4vpEGhEhuoOqqowfP56tW7cyZMgQrFYr8+fP591336WsrIwFCxZw/vx5li1bBsSS2FVWVsaff/ToUaZMmQJAdnY2Y8eOjT82ceJEAAYPHkwwGOy6NyVEG6SnIcQlmDdvHi+99FL8HIXp06fz0UcfATB69GhGjBjByy+/TElJCUuWLInn+gIYN24c+/btA6Curi6eMBBoktI+sUzmNER3k6AhxCX43Oc+x+7du/mnf/ongPjBPDNnziQ7O5uvfvWrFBcXs3jxYrZu3cpll10Wf+6CBQsYOHAgd999N9/5znew2+1YLJZWX2vGjBksW7YMSRcnupMkLBSimxw5coSysjK+9KUvUVNTwy233MI777yD1Wrt7qoJ0SoJGkJ0E7/fz7e+9S3OnTuHpmksWbKE22+/vburJURSEjSEEEKkTOY0hBBCpEyChhBCiJRJ0BBCCJEyCRpCCCFSJkFDCCFEyv4/i/qR2QhALjUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"Weight\",y=\"Price\",data=testing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "8ab03b1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Weight', ylabel='Price'>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"Weight\",y=\"Price\",data=testing)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3da5ce1f",
   "metadata": {},
   "source": [
    "## Ridge Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "7e627243",
   "metadata": {},
   "outputs": [],
   "source": [
    "rd = Ridge(0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "229957f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The model training is completed\n"
     ]
    }
   ],
   "source": [
    "model_train_1 = rd.fit(x_train,y_train)\n",
    "print(\"The model training is completed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "92884d79",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of the training data - \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.6264743463447533"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Accuracy of the training data - \")\n",
    "model_train_1.score(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "6db1a7df",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([11348.21057535, 11313.924114  , 16186.9427243 ,  8593.39845144,\n",
       "       13422.95469733,  9283.6491104 ,  9426.21546166, 10841.82370521,\n",
       "        9643.3150007 , 10436.51591113, 10613.07613928, 14951.55379001,\n",
       "        8997.2340068 , 12937.50390955, 10058.47650535, 15251.2450415 ,\n",
       "        8314.79818581, 11174.28558233,  8392.29829237,  6629.13505954,\n",
       "       12217.66947582, 11493.94065336, 10517.92112241,  5049.08243534,\n",
       "        9760.89203118,  3829.95013057,  6183.66129215,  8697.52173823,\n",
       "        8216.4015412 , 15092.41249627,  7873.17627317, 10048.14642272,\n",
       "       13717.648245  , 10861.95840832, 16016.56044279, 10199.63063551,\n",
       "        5636.89906342,  9169.25920961, 14905.60977111, 10476.09464124,\n",
       "       13078.89915064,  8215.82290168,  9646.97093288,  5560.86289888,\n",
       "       12282.2217504 , 11982.55659786, 11881.42472437, 11859.41225379,\n",
       "       10764.65982488,  9536.99879676, 12371.35532077,  8310.20373183,\n",
       "        6382.91331749,  6995.69091694,  9860.40318576, 12572.62561822,\n",
       "       14121.43433204, 11791.95592487,  9847.35633388,  9516.66713813,\n",
       "        9726.03566855,  8498.96304785, 12572.1689824 , 11149.37615252,\n",
       "       10823.99998214, 10594.83135252, 12106.79367665,  7310.4607513 ,\n",
       "       10625.1096835 , 12395.50064979, 10208.34340864, 12892.38995319,\n",
       "       10647.73441037, 10545.78667963, 12563.09234701,  8436.028898  ,\n",
       "       12092.67818549,  8942.96747025,  7860.8356906 ,  9214.09665212,\n",
       "       11619.92582037, 17416.12061007,  8603.91890812,  7883.91511743,\n",
       "        9005.5931127 ,  9215.97767571, 12944.86636737,  9305.48424565,\n",
       "       10791.61764525, 11772.06279416,  5522.9695019 ,  9547.55029887,\n",
       "        7779.7421124 , 10067.13340267,  8064.07552954, 11482.31362029,\n",
       "       10924.23416468, 13805.2335875 ,  9750.09427922,  8774.85248783,\n",
       "        5857.78823033,  8304.33940825,  9071.27702073, 11519.146666  ,\n",
       "       10382.91363299, 10847.09146111, 11158.15551746, 10152.10312395,\n",
       "        9334.12320816, 11340.5157046 , 11822.4139249 ,  9718.92896799,\n",
       "        7311.21773426, 18026.15581221, 10195.20224613,  9116.17232904,\n",
       "       10750.41234644, 11418.013063  ,  9506.16691711,  8553.37965381,\n",
       "        8108.05104885,  5118.80075205,  9405.29236373, 12672.90790439,\n",
       "       14905.60977111,  6661.3144831 ,  8751.32588781, 12452.38261244,\n",
       "       10826.10623851,  7161.4272029 , 11603.54077965, 13734.52167784,\n",
       "       16156.9957411 ,  6458.78437821, 11161.16595783,  9536.75991306,\n",
       "        6250.06492836, 10369.90220729,  9255.35479485, 11135.26040089,\n",
       "       17180.25352056,  8384.16086641, 13024.29825767, 13597.00179841,\n",
       "        7600.90773995, 12755.16523718, 13627.59833359, 16488.29462181,\n",
       "       11056.93326368, 10782.15863894, 12256.14215049, 10376.43763446,\n",
       "        8230.84586921,  8469.79510657,  8840.74683887, 11115.42234133,\n",
       "        8198.57424205,  8457.19322391,  8913.68578735,  7726.15374566,\n",
       "        9609.23846142,  9320.37695541,  6272.09616554,  9928.45121446,\n",
       "       10474.21257575,  7568.22709071, 16014.5123127 ,  9488.12149085,\n",
       "        6879.77782484, 11524.23905332, 11513.42712949, 15367.08178491,\n",
       "       10577.89143751, 15464.08450622, 12460.36594736, 11611.53367903,\n",
       "       14380.43715133, 12257.58033514, 15779.8840241 ,  7900.68542608,\n",
       "       11255.34584139, 11547.15596838,  7638.97286157,  9729.78155387,\n",
       "       15824.92189224,  8777.14331494,  8889.6602121 , 10788.84990188,\n",
       "        9858.81374951, 10246.01879572,  8939.48063456,  9276.0900297 ,\n",
       "        8426.8364372 , 10133.37698354, 11771.06744845, 11812.33986   ,\n",
       "       10537.70460853, 10857.76514881, 10871.2730388 ,  9160.30892488,\n",
       "        8895.36228438,  6638.39678662, 10999.91801085, 11909.10215801,\n",
       "        7633.93661054, 10486.72277576, 13189.60888521, 11546.49116578,\n",
       "       12565.63017159, 13923.87255021, 11037.63514835,  9410.40221528,\n",
       "       12563.02823235, 10559.49340917, 12279.42983339, 11279.93622549,\n",
       "       12122.25307165,  8600.81903555,  8055.53752546,  9726.12588216,\n",
       "       11649.50685752,  7870.68937793,  7639.60955198, 11474.1431589 ,\n",
       "        9942.19616483, 10404.00158696,  8504.16891632, 10768.64511485,\n",
       "       14242.29187546, 10992.20214628, 10670.53449152, 11028.70280231,\n",
       "       29416.56166118, 13100.85482055, 10093.02547749, 11123.96800797,\n",
       "       12924.38783789, 15201.98075251,  9150.62208357, 12325.16888857,\n",
       "        9742.75440131, 11985.19976657, 11502.6847324 , 11199.47756867,\n",
       "       11168.52893661,  8915.86339378,  7787.3011931 , 12602.84937576,\n",
       "        9516.0020983 ,  9532.60526613, 17362.92458261, 15090.52886794,\n",
       "        6674.4112672 , 11809.68230543,  9763.26899811, 23006.374481  ,\n",
       "       12574.23090937, 13988.65587355, 11364.04258834, 14333.05286399,\n",
       "        9869.21743268, 14159.70241347, 10629.11622777, 10159.74157469,\n",
       "        8115.24310782, 10726.13203258,  8528.91003105,  9689.22520275,\n",
       "        9756.21011389,  8943.93174942,  8549.79299899, 11493.32923888,\n",
       "       14279.03787804, 12768.17337052,  9738.80465771,  8837.68355456,\n",
       "       11812.30552221,  9725.79375296, 12312.4235265 ,  9106.28335583,\n",
       "       14860.64062505, 12047.34254918,  8966.54639325, 13940.341918  ,\n",
       "        6916.0581033 , 11198.97489504, 10353.59458041,  9026.44339154])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_1 = model_train_1.predict(X_test)\n",
    "pred_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "2d7a9ae2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7101741813949078"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ridg_r2 = r2_score(y_test,pred_1)\n",
    "ridg_r2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "e2051eac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Prep_Models</th>\n",
       "      <th>Rsquared</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1st_Model</td>\n",
       "      <td>0.710174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2nd_Model</td>\n",
       "      <td>0.710174</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Prep_Models  Rsquared\n",
       "0   1st_Model  0.710174\n",
       "1   2nd_Model  0.710174"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d2={'Prep_Models':['1st_Model','2nd_Model'],'Rsquared':[mltpl_r2,ridg_r2]}\n",
    "table=pd.DataFrame(d2)\n",
    "table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65995736",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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