Predicting Insurance Charges using XGBoost and Random Forest ML Models.ipynb

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  {
   "cell_type": "markdown",
   "id": "0fd22984",
   "metadata": {},
   "source": [
    "The notebook presents an approach to predict health insurance prices for people with varying attributes. We will try to use multiple models including XGBoost to experiment and find the best one. The source of the dataset is here - https://www.kaggle.com/datasets/mirichoi0218/insurance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d18a6a62",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8048b53a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ae3701d",
   "metadata": {},
   "source": [
    "### Data load and exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fb621339",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read data\n",
    "df_raw = pd.read_csv(\"Dataset/insurance.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "71db0d0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>27.900</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>16884.92400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>33.770</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1725.55230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28</td>\n",
       "      <td>male</td>\n",
       "      <td>33.000</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>4449.46200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>male</td>\n",
       "      <td>22.705</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>21984.47061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>32</td>\n",
       "      <td>male</td>\n",
       "      <td>28.880</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>3866.85520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   age     sex     bmi  children smoker     region      charges\n",
       "0   19  female  27.900         0    yes  southwest  16884.92400\n",
       "1   18    male  33.770         1     no  southeast   1725.55230\n",
       "2   28    male  33.000         3     no  southeast   4449.46200\n",
       "3   33    male  22.705         0     no  northwest  21984.47061\n",
       "4   32    male  28.880         0     no  northwest   3866.85520"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Explore data\n",
    "df_raw.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4df23c70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1338, 7)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the shape of the dataframe\n",
    "df_raw.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5ac905bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .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>age</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>39.207025</td>\n",
       "      <td>30.663397</td>\n",
       "      <td>1.094918</td>\n",
       "      <td>13270.422265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14.049960</td>\n",
       "      <td>6.098187</td>\n",
       "      <td>1.205493</td>\n",
       "      <td>12110.011237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>15.960000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1121.873900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>27.000000</td>\n",
       "      <td>26.296250</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4740.287150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>39.000000</td>\n",
       "      <td>30.400000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9382.033000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>51.000000</td>\n",
       "      <td>34.693750</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>16639.912515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>64.000000</td>\n",
       "      <td>53.130000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>63770.428010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "               age          bmi     children       charges\n",
       "count  1338.000000  1338.000000  1338.000000   1338.000000\n",
       "mean     39.207025    30.663397     1.094918  13270.422265\n",
       "std      14.049960     6.098187     1.205493  12110.011237\n",
       "min      18.000000    15.960000     0.000000   1121.873900\n",
       "25%      27.000000    26.296250     0.000000   4740.287150\n",
       "50%      39.000000    30.400000     1.000000   9382.033000\n",
       "75%      51.000000    34.693750     2.000000  16639.912515\n",
       "max      64.000000    53.130000     5.000000  63770.428010"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check numerical features stats\n",
    "df_raw.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "83172571",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age         0\n",
       "sex         0\n",
       "bmi         0\n",
       "children    0\n",
       "smoker      0\n",
       "region      0\n",
       "charges     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check for missing values\n",
    "df_raw.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "66b9b6ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1338 entries, 0 to 1337\n",
      "Data columns (total 7 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   age       1338 non-null   int64  \n",
      " 1   sex       1338 non-null   object \n",
      " 2   bmi       1338 non-null   float64\n",
      " 3   children  1338 non-null   int64  \n",
      " 4   smoker    1338 non-null   object \n",
      " 5   region    1338 non-null   object \n",
      " 6   charges   1338 non-null   float64\n",
      "dtypes: float64(2), int64(2), object(3)\n",
      "memory usage: 73.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df_raw.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18ec63d9",
   "metadata": {},
   "source": [
    "### Performing data visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "325a8374",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['southwest', 'southeast', 'northwest', 'northeast'], dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets see the distribution of people across the categorical variables\n",
    "df_raw['region'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e90ebb6a",
   "metadata": {},
   "outputs": [
    {
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   ],
   "source": [
    "fig = px.histogram(df_raw, x = 'region', title = \"People per region\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff921218",
   "metadata": {},
   "source": [
    "We can see that its a fairly uniformly distributed dataset across region\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "50c12c9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'sex', 'bmi', 'children', 'smoker', 'region', 'charges'], dtype='object')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df_raw.columns"
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  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e7e8ce05",
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.histogram(data_frame = df_raw, x = 'sex', color = 'smoker', title = 'Distribution of sex and smoker')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "2da0f084",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='region', ylabel='charges'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Lets now visualize the distribution of charges across regions\n",
    "sns.boxplot(data = df_raw, x = 'region', y = 'charges')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a083f441",
   "metadata": {},
   "source": [
    "Its evident from above plot that the median charge though is similar across the various regions but the 75th percentile is quite high for southeast region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "ef8f567a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='region', ylabel='charges'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Lets now add the attribute smoker to the above chart to understand if it has any impact or not\n",
    "sns.boxplot(data = df_raw, x = 'region', y = 'charges', hue = 'smoker')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "027d0188",
   "metadata": {},
   "source": [
    "We can observe that the median charges for smokers in southeast and southwest is significantly higher compared to the other two regions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "24a1715c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1338 entries, 0 to 1337\n",
      "Data columns (total 7 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   age       1338 non-null   int64  \n",
      " 1   sex       1338 non-null   object \n",
      " 2   bmi       1338 non-null   float64\n",
      " 3   children  1338 non-null   int64  \n",
      " 4   smoker    1338 non-null   object \n",
      " 5   region    1338 non-null   object \n",
      " 6   charges   1338 non-null   float64\n",
      "dtypes: float64(2), int64(2), object(3)\n",
      "memory usage: 73.3+ KB\n"
     ]
    }
   ],
   "source": [
    "# Understanding the correlation between the features\n",
    "df_raw.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "347e5938",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x25543a769d0>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatterplots for joint relationships and checking univariate analysis\n",
    "sns.pairplot(df_raw)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dee0061b",
   "metadata": {},
   "source": [
    "We can observe some positive correlation between charges and age"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d73ba2b",
   "metadata": {},
   "source": [
    "### Data preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "601b7191",
   "metadata": {},
   "source": [
    "Since this is a small dataset we can try to encode the categorical variables using one hot encoding technique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "19152e85",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dum = pd.get_dummies(df_raw, columns = ['sex', 'region', 'smoker'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "baed5ccf",
   "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>age</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>charges</th>\n",
       "      <th>sex_female</th>\n",
       "      <th>sex_male</th>\n",
       "      <th>region_northeast</th>\n",
       "      <th>region_northwest</th>\n",
       "      <th>region_southeast</th>\n",
       "      <th>region_southwest</th>\n",
       "      <th>smoker_no</th>\n",
       "      <th>smoker_yes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>27.900</td>\n",
       "      <td>0</td>\n",
       "      <td>16884.92400</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>33.770</td>\n",
       "      <td>1</td>\n",
       "      <td>1725.55230</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28</td>\n",
       "      <td>33.000</td>\n",
       "      <td>3</td>\n",
       "      <td>4449.46200</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>22.705</td>\n",
       "      <td>0</td>\n",
       "      <td>21984.47061</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>32</td>\n",
       "      <td>28.880</td>\n",
       "      <td>0</td>\n",
       "      <td>3866.85520</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age     bmi  children      charges  sex_female  sex_male  region_northeast   \n",
       "0   19  27.900         0  16884.92400        True     False             False  \\\n",
       "1   18  33.770         1   1725.55230       False      True             False   \n",
       "2   28  33.000         3   4449.46200       False      True             False   \n",
       "3   33  22.705         0  21984.47061       False      True             False   \n",
       "4   32  28.880         0   3866.85520       False      True             False   \n",
       "\n",
       "   region_northwest  region_southeast  region_southwest  smoker_no  smoker_yes  \n",
       "0             False             False              True      False        True  \n",
       "1             False              True             False       True       False  \n",
       "2             False              True             False       True       False  \n",
       "3              True             False             False       True       False  \n",
       "4              True             False             False       True       False  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_dum.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "3513c4b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now we need to split the data into the features or independant variable list and target or dependant variable\n",
    "X = df_dum.drop('charges', axis = 1)\n",
    "y = df_dum['charges']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "dac65bd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.array(X)\n",
    "y = np.array(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "ceaf2401",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Additional library\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "141ba646",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "f0c8ba43",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1070, 11)"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18ff38aa",
   "metadata": {},
   "source": [
    "### Model Building"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dce5a8d",
   "metadata": {},
   "source": [
    "We will first try to build a linear regression model using sklearn's LinearRegression class\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "fe63dd35",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing additional libraries\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error, accuracy_score\n",
    "from math import sqrt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "12897538",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fitting our data with the model\n",
    "LinearRegModel = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "526b33c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LinearRegression</label><div class=\"sk-toggleable__content\"><pre>LinearRegression()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LinearRegModel.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "8f4992f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Linear Regression Model =  0.746796161128958\n"
     ]
    }
   ],
   "source": [
    "LinearRegModel_score = LinearRegModel.score(X_test, y_test)\n",
    "print(\"Accuracy of Linear Regression Model = \",LinearRegModel_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fba7a089",
   "metadata": {},
   "source": [
    "Now we will also try to build a decision tree and Random forest model to do the predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "f4d6fa79",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing libraries\n",
    "from sklearn.tree import DecisionTreeRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "34769d17",
   "metadata": {},
   "outputs": [],
   "source": [
    "DecisionTreeModel = DecisionTreeRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "3c860c64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeRegressor()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeRegressor</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeRegressor()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "DecisionTreeRegressor()"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DecisionTreeModel.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "dbfc5a56",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Decision Tree Model =  0.6978930623332613\n"
     ]
    }
   ],
   "source": [
    "DecisionTreeModel_score = DecisionTreeModel.score(X_test, y_test)\n",
    "print(\"Accuracy of Decision Tree Model = \",DecisionTreeModel_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4110bdf1",
   "metadata": {},
   "source": [
    "We will now try using a Random Forest Regressor and also use the Grid Search "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "77e0b80e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing libraries\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "684bff49",
   "metadata": {},
   "outputs": [],
   "source": [
    "param_grid = {\n",
    "    'n_estimators' : [5, 10, 30],\n",
    "    'max_depth' : [5, 10, 15],\n",
    "    'min_samples_split' : [2, 5, 10],\n",
    "    'min_samples_leaf' : [1, 2, 4]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "91459733",
   "metadata": {},
   "outputs": [],
   "source": [
    "RandomForestRegModel = RandomForestRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "af143687",
   "metadata": {},
   "outputs": [],
   "source": [
    "grid_search = GridSearchCV(RandomForestRegModel, param_grid = param_grid, cv= 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "2e45999a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-14 {color: black;background-color: white;}#sk-container-id-14 pre{padding: 0;}#sk-container-id-14 div.sk-toggleable {background-color: white;}#sk-container-id-14 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-14 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-14 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-14 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-14 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-14 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-14 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-14 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-14 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-14 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-14 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-14 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-14 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-14 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-14 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-14 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-14 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-14 div.sk-item {position: relative;z-index: 1;}#sk-container-id-14 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-14 div.sk-item::before, #sk-container-id-14 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-14 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-14 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-14 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-14 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-14 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-14 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-14 div.sk-label-container {text-align: center;}#sk-container-id-14 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-14 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-14\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=5, estimator=RandomForestRegressor(),\n",
       "             param_grid={&#x27;max_depth&#x27;: [5, 10, 15],\n",
       "                         &#x27;min_samples_leaf&#x27;: [1, 2, 4],\n",
       "                         &#x27;min_samples_split&#x27;: [2, 5, 10],\n",
       "                         &#x27;n_estimators&#x27;: [5, 10, 30]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-14\" type=\"checkbox\" ><label for=\"sk-estimator-id-14\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GridSearchCV</label><div class=\"sk-toggleable__content\"><pre>GridSearchCV(cv=5, estimator=RandomForestRegressor(),\n",
       "             param_grid={&#x27;max_depth&#x27;: [5, 10, 15],\n",
       "                         &#x27;min_samples_leaf&#x27;: [1, 2, 4],\n",
       "                         &#x27;min_samples_split&#x27;: [2, 5, 10],\n",
       "                         &#x27;n_estimators&#x27;: [5, 10, 30]})</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-15\" type=\"checkbox\" ><label for=\"sk-estimator-id-15\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: RandomForestRegressor</label><div class=\"sk-toggleable__content\"><pre>RandomForestRegressor()</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-16\" type=\"checkbox\" ><label for=\"sk-estimator-id-16\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestRegressor</label><div class=\"sk-toggleable__content\"><pre>RandomForestRegressor()</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(cv=5, estimator=RandomForestRegressor(),\n",
       "             param_grid={'max_depth': [5, 10, 15],\n",
       "                         'min_samples_leaf': [1, 2, 4],\n",
       "                         'min_samples_split': [2, 5, 10],\n",
       "                         'n_estimators': [5, 10, 30]})"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "b8a136c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_depth': 5,\n",
       " 'min_samples_leaf': 4,\n",
       " 'min_samples_split': 2,\n",
       " 'n_estimators': 30}"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "c5e62702",
   "metadata": {},
   "outputs": [],
   "source": [
    "best_params = grid_search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "18c7c376",
   "metadata": {},
   "outputs": [],
   "source": [
    "RandomForestRegModel = RandomForestRegressor(**best_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "ceb5376b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-15 {color: black;background-color: white;}#sk-container-id-15 pre{padding: 0;}#sk-container-id-15 div.sk-toggleable {background-color: white;}#sk-container-id-15 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-15 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-15 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-15 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-15 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-15 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-15 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-15 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-15 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-15 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-15 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-15 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-15 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-15 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-15 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-15 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-15 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-15 div.sk-item {position: relative;z-index: 1;}#sk-container-id-15 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-15 div.sk-item::before, #sk-container-id-15 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-15 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-15 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-15 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-15 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-15 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-15 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-15 div.sk-label-container {text-align: center;}#sk-container-id-15 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-15 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-15\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestRegressor(max_depth=5, min_samples_leaf=4, n_estimators=30)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-17\" type=\"checkbox\" checked><label for=\"sk-estimator-id-17\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestRegressor</label><div class=\"sk-toggleable__content\"><pre>RandomForestRegressor(max_depth=5, min_samples_leaf=4, n_estimators=30)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestRegressor(max_depth=5, min_samples_leaf=4, n_estimators=30)"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RandomForestRegModel.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "b77ea45c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of Decision Tree Model =  0.8571684460542175\n"
     ]
    }
   ],
   "source": [
    "RandomForestRegModel_score = RandomForestRegModel.score(X_test, y_test)\n",
    "print(\"Accuracy of Decision Tree Model = \",RandomForestRegModel_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "995983d9",
   "metadata": {},
   "source": [
    "Now we are going to build the XGBoost regressor model for predicting the charges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "c17dac02",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing libraries\n",
    "from xgboost import XGBRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "a14fa65a",
   "metadata": {},
   "outputs": [],
   "source": [
    "param_grid = {\n",
    "    'n_estimators' : [5, 10, 30],\n",
    "    'max_depth' : [5, 10, 15]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "ec2ee7af",
   "metadata": {},
   "outputs": [],
   "source": [
    "XGBRegressorModel = XGBRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "1fd6726e",
   "metadata": {},
   "outputs": [],
   "source": [
    "gridSearch = GridSearchCV(XGBRegressorModel,  param_grid = param_grid, cv= 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "c79f8ba4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-18 {color: black;background-color: white;}#sk-container-id-18 pre{padding: 0;}#sk-container-id-18 div.sk-toggleable {background-color: white;}#sk-container-id-18 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-18 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-18 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-18 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-18 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-18 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-18 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-18 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-18 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-18 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-18 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-18 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-18 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-18 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-18 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-18 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-18 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-18 div.sk-item {position: relative;z-index: 1;}#sk-container-id-18 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-18 div.sk-item::before, #sk-container-id-18 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-18 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-18 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-18 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-18 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-18 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-18 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-18 div.sk-label-container {text-align: center;}#sk-container-id-18 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-18 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-18\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=5,\n",
       "             estimator=XGBRegressor(base_score=None, booster=None,\n",
       "                                    callbacks=None, colsample_bylevel=None,\n",
       "                                    colsample_bynode=None,\n",
       "                                    colsample_bytree=None,\n",
       "                                    early_stopping_rounds=None,\n",
       "                                    enable_categorical=False, eval_metric=None,\n",
       "                                    feature_types=None, gamma=None, gpu_id=None,\n",
       "                                    grow_policy=None, importance_type=None,\n",
       "                                    interaction_constraints=None,\n",
       "                                    learning_rate=None, max_bin=None,\n",
       "                                    max_cat_threshold=None,\n",
       "                                    max_cat_to_onehot=None, max_delta_step=None,\n",
       "                                    max_depth=None, max_leaves=None,\n",
       "                                    min_child_weight=None, missing=nan,\n",
       "                                    monotone_constraints=None, n_estimators=100,\n",
       "                                    n_jobs=None, num_parallel_tree=None,\n",
       "                                    predictor=None, random_state=None, ...),\n",
       "             param_grid={&#x27;max_depth&#x27;: [5, 10, 15], &#x27;n_estimators&#x27;: [5, 10, 30]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-20\" type=\"checkbox\" ><label for=\"sk-estimator-id-20\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GridSearchCV</label><div class=\"sk-toggleable__content\"><pre>GridSearchCV(cv=5,\n",
       "             estimator=XGBRegressor(base_score=None, booster=None,\n",
       "                                    callbacks=None, colsample_bylevel=None,\n",
       "                                    colsample_bynode=None,\n",
       "                                    colsample_bytree=None,\n",
       "                                    early_stopping_rounds=None,\n",
       "                                    enable_categorical=False, eval_metric=None,\n",
       "                                    feature_types=None, gamma=None, gpu_id=None,\n",
       "                                    grow_policy=None, importance_type=None,\n",
       "                                    interaction_constraints=None,\n",
       "                                    learning_rate=None, max_bin=None,\n",
       "                                    max_cat_threshold=None,\n",
       "                                    max_cat_to_onehot=None, max_delta_step=None,\n",
       "                                    max_depth=None, max_leaves=None,\n",
       "                                    min_child_weight=None, missing=nan,\n",
       "                                    monotone_constraints=None, n_estimators=100,\n",
       "                                    n_jobs=None, num_parallel_tree=None,\n",
       "                                    predictor=None, random_state=None, ...),\n",
       "             param_grid={&#x27;max_depth&#x27;: [5, 10, 15], &#x27;n_estimators&#x27;: [5, 10, 30]})</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-21\" type=\"checkbox\" ><label for=\"sk-estimator-id-21\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: XGBRegressor</label><div class=\"sk-toggleable__content\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, gpu_id=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             n_estimators=100, n_jobs=None, num_parallel_tree=None,\n",
       "             predictor=None, random_state=None, ...)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-22\" type=\"checkbox\" ><label for=\"sk-estimator-id-22\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBRegressor</label><div class=\"sk-toggleable__content\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, gpu_id=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             n_estimators=100, n_jobs=None, num_parallel_tree=None,\n",
       "             predictor=None, random_state=None, ...)</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(cv=5,\n",
       "             estimator=XGBRegressor(base_score=None, booster=None,\n",
       "                                    callbacks=None, colsample_bylevel=None,\n",
       "                                    colsample_bynode=None,\n",
       "                                    colsample_bytree=None,\n",
       "                                    early_stopping_rounds=None,\n",
       "                                    enable_categorical=False, eval_metric=None,\n",
       "                                    feature_types=None, gamma=None, gpu_id=None,\n",
       "                                    grow_policy=None, importance_type=None,\n",
       "                                    interaction_constraints=None,\n",
       "                                    learning_rate=None, max_bin=None,\n",
       "                                    max_cat_threshold=None,\n",
       "                                    max_cat_to_onehot=None, max_delta_step=None,\n",
       "                                    max_depth=None, max_leaves=None,\n",
       "                                    min_child_weight=None, missing=nan,\n",
       "                                    monotone_constraints=None, n_estimators=100,\n",
       "                                    n_jobs=None, num_parallel_tree=None,\n",
       "                                    predictor=None, random_state=None, ...),\n",
       "             param_grid={'max_depth': [5, 10, 15], 'n_estimators': [5, 10, 30]})"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gridSearch.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "3f6990aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "best_params = gridSearch.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "d8b04168",
   "metadata": {},
   "outputs": [],
   "source": [
    "XGBRegressorModel = XGBRegressor(**best_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "05fc6027",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-19 {color: black;background-color: white;}#sk-container-id-19 pre{padding: 0;}#sk-container-id-19 div.sk-toggleable {background-color: white;}#sk-container-id-19 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-19 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-19 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-19 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-19 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-19 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-19 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-19 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-19 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-19 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-19 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-19 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-19 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-19 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-19 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-19 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-19 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-19 div.sk-item {position: relative;z-index: 1;}#sk-container-id-19 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-19 div.sk-item::before, #sk-container-id-19 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-19 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-19 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-19 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-19 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-19 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-19 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-19 div.sk-label-container {text-align: center;}#sk-container-id-19 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-19 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-19\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, gpu_id=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=5, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             n_estimators=10, n_jobs=None, num_parallel_tree=None,\n",
       "             predictor=None, random_state=None, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-23\" type=\"checkbox\" checked><label for=\"sk-estimator-id-23\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBRegressor</label><div class=\"sk-toggleable__content\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, gpu_id=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=5, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             n_estimators=10, n_jobs=None, num_parallel_tree=None,\n",
       "             predictor=None, random_state=None, ...)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
       "             colsample_bylevel=None, colsample_bynode=None,\n",
       "             colsample_bytree=None, early_stopping_rounds=None,\n",
       "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "             gamma=None, gpu_id=None, grow_policy=None, importance_type=None,\n",
       "             interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "             max_delta_step=None, max_depth=5, max_leaves=None,\n",
       "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "             n_estimators=10, n_jobs=None, num_parallel_tree=None,\n",
       "             predictor=None, random_state=None, ...)"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "XGBRegressorModel.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "8f7f5452",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8501963335000873"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "XGBRegressorModel.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19e8a475",
   "metadata": {},
   "source": [
    "Lets try to visualize the predicted results of the XGBoostRegressor Model and the Linear Regressor model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "d7f0e716",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Linear Regression Model'),\n",
       " Text(0.5, 0, 'Predicted Charges'),\n",
       " Text(0, 0.5, 'Actual Charges')]"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_predict_linear = LinearRegModel.predict(X_test)\n",
    "\n",
    "fig = sns.regplot(x = y_predict_linear, y = y_test, color = 'red', marker = \"^\")\n",
    "fig.set(title = \"Linear Regression Model\", \n",
    "        xlabel = \"Predicted Charges\", \n",
    "        ylabel = \"Actual Charges\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "fe2d108f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'XGB Regression Model'),\n",
       " Text(0.5, 0, 'Predicted Charges'),\n",
       " Text(0, 0.5, 'Actual Charges')]"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_predict_xgb = XGBRegressorModel.predict(X_test)\n",
    "\n",
    "fig = sns.regplot(x = y_predict_xgb, y = y_test, color = 'red', marker = \"^\")\n",
    "fig.set(title = \"XGB Regression Model\", \n",
    "        xlabel = \"Predicted Charges\", \n",
    "        ylabel = \"Actual Charges\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "691e765e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}