Assignments/Week #6/Homework.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7bce97a4",
   "metadata": {},
   "source": [
    "The goal of this homework is to create a regression model for predicting housing prices (column 'median_house_value').\n",
    "\n",
    "In this homework we'll again use the California Housing Prices dataset - the same one we used in homework 2 and 3."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea728dcb",
   "metadata": {},
   "source": [
    "You can take it from Kaggle or download using wget link mentioned below:\n",
    "\n",
    "wget https://raw.githubusercontent.com/alexeygrigorev/datasets/master/housing.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66d87f4e",
   "metadata": {},
   "source": [
    "Note: sometimes your answer doesn't match one of the options exactly. That's fine. Select the option that's closest to your solution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3e614e79",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "--2022-10-17 23:45:28--  https://raw.githubusercontent.com/alexeygrigorev/datasets/master/housing.csv\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 2606:50c0:8002::154, 2606:50c0:8001::154, 2606:50c0:8003::154, ...\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|2606:50c0:8002::154|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 1423529 (1.4M) [text/plain]\n",
      "Saving to: 'housing.csv'\n",
      "\n",
      "     0K .......... .......... .......... .......... ..........  3%  680K 2s\n",
      "    50K .......... .......... .......... .......... ..........  7% 2.30M 1s\n",
      "   100K .......... .......... .......... .......... .......... 10% 1.25M 1s\n",
      "   150K .......... .......... .......... .......... .......... 14% 3.84M 1s\n",
      "   200K .......... .......... .......... .......... .......... 17% 1.13M 1s\n",
      "   250K .......... .......... .......... .......... .......... 21% 3.73M 1s\n",
      "   300K .......... .......... .......... .......... .......... 25% 2.55M 1s\n",
      "   350K .......... .......... .......... .......... .......... 28% 1.51M 1s\n",
      "   400K .......... .......... .......... .......... .......... 32% 3.46M 1s\n",
      "   450K .......... .......... .......... .......... .......... 35% 7.29M 0s\n",
      "   500K .......... .......... .......... .......... .......... 39% 8.67M 0s\n",
      "   550K .......... .......... .......... .......... .......... 43% 9.48M 0s\n",
      "   600K .......... .......... .......... .......... .......... 46% 2.00M 0s\n",
      "   650K .......... .......... .......... .......... .......... 50% 8.38M 0s\n",
      "   700K .......... .......... .......... .......... .......... 53% 10.4M 0s\n",
      "   750K .......... .......... .......... .......... .......... 57% 11.8M 0s\n",
      "   800K .......... .......... .......... .......... .......... 61% 6.12M 0s\n",
      "   850K .......... .......... .......... .......... .......... 64% 11.3M 0s\n",
      "   900K .......... .......... .......... .......... .......... 68% 12.5M 0s\n",
      "   950K .......... .......... .......... .......... .......... 71% 26.8M 0s\n",
      "  1000K .......... .......... .......... .......... .......... 75% 8.16M 0s\n",
      "  1050K .......... .......... .......... .......... .......... 79% 43.7M 0s\n",
      "  1100K .......... .......... .......... .......... .......... 82% 24.7M 0s\n",
      "  1150K .......... .......... .......... .......... .......... 86% 2.72M 0s\n",
      "  1200K .......... .......... .......... .......... .......... 89% 11.1M 0s\n",
      "  1250K .......... .......... .......... .......... .......... 93% 8.86M 0s\n",
      "  1300K .......... .......... .......... .......... .......... 97% 50.3M 0s\n",
      "  1350K .......... .......... .......... ..........           100% 21.1M=0.4s\n",
      "\n",
      "2022-10-17 23:45:29 (3.54 MB/s) - 'housing.csv' saved [1423529/1423529]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget \"https://raw.githubusercontent.com/alexeygrigorev/datasets/master/housing.csv\" "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3065c211",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import sklearn\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.feature_extraction import DictVectorizer\n",
    "\n",
    "from sklearn.tree import DecisionTreeRegressor \n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "from sklearn.metrics import r2_score, mean_squared_error\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "75db4337",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89b8f9d7",
   "metadata": {},
   "source": [
    "# Loading the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fde00dc7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "0    -122.23     37.88                41.0        880.0           129.0   \n",
       "1    -122.22     37.86                21.0       7099.0          1106.0   \n",
       "2    -122.24     37.85                52.0       1467.0           190.0   \n",
       "3    -122.25     37.85                52.0       1274.0           235.0   \n",
       "4    -122.25     37.85                52.0       1627.0           280.0   \n",
       "\n",
       "   population  households  median_income  median_house_value ocean_proximity  \n",
       "0       322.0       126.0         8.3252            452600.0        NEAR BAY  \n",
       "1      2401.0      1138.0         8.3014            358500.0        NEAR BAY  \n",
       "2       496.0       177.0         7.2574            352100.0        NEAR BAY  \n",
       "3       558.0       219.0         5.6431            341300.0        NEAR BAY  \n",
       "4       565.0       259.0         3.8462            342200.0        NEAR BAY  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"housing.csv\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "da5a566d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20640, 10)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6b255639",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 20640 entries, 0 to 20639\n",
      "Data columns (total 10 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   longitude           20640 non-null  float64\n",
      " 1   latitude            20640 non-null  float64\n",
      " 2   housing_median_age  20640 non-null  float64\n",
      " 3   total_rooms         20640 non-null  float64\n",
      " 4   total_bedrooms      20433 non-null  float64\n",
      " 5   population          20640 non-null  float64\n",
      " 6   households          20640 non-null  float64\n",
      " 7   median_income       20640 non-null  float64\n",
      " 8   median_house_value  20640 non-null  float64\n",
      " 9   ocean_proximity     20640 non-null  object \n",
      "dtypes: float64(9), object(1)\n",
      "memory usage: 1.6+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87e8f07b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b8f5ae94",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1e6c4c89",
   "metadata": {},
   "source": [
    "Use only the following columns:\n",
    "\n",
    "    'latitude',\n",
    "\n",
    "    'longitude',\n",
    "\n",
    "    'housing_median_age',\n",
    "\n",
    "    'total_rooms',\n",
    "\n",
    "    'total_bedrooms',\n",
    "\n",
    "    'population',\n",
    "\n",
    "    'households',\n",
    "\n",
    "    'median_income',\n",
    "\n",
    "    'median_house_value',\n",
    "\n",
    "    'ocean_proximity'\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0cf69cc1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['longitude', 'latitude', 'housing_median_age', 'total_rooms',\n",
       "       'total_bedrooms', 'population', 'households', 'median_income',\n",
       "       'median_house_value', 'ocean_proximity'], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = data.columns.values\n",
    "cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a589c6c4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "54ba1c61",
   "metadata": {},
   "source": [
    "#### Fill NAs with 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fa6cdb6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "longitude               0\n",
       "latitude                0\n",
       "housing_median_age      0\n",
       "total_rooms             0\n",
       "total_bedrooms        207\n",
       "population              0\n",
       "households              0\n",
       "median_income           0\n",
       "median_house_value      0\n",
       "ocean_proximity         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1fb79f03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "longitude             0\n",
       "latitude              0\n",
       "housing_median_age    0\n",
       "total_rooms           0\n",
       "total_bedrooms        0\n",
       "population            0\n",
       "households            0\n",
       "median_income         0\n",
       "median_house_value    0\n",
       "ocean_proximity       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.total_bedrooms = data.total_bedrooms.fillna(0)\n",
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f27843ad",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8fbb5a9b",
   "metadata": {},
   "source": [
    "#### Apply the log tranform to median_house_value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "374c290a",
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"median_house_value\"] = np.log1p(data[\"median_house_value\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "dc80737a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>13.022766</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>12.789687</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>12.771673</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>12.740520</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>12.743154</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "0    -122.23     37.88                41.0        880.0           129.0   \n",
       "1    -122.22     37.86                21.0       7099.0          1106.0   \n",
       "2    -122.24     37.85                52.0       1467.0           190.0   \n",
       "3    -122.25     37.85                52.0       1274.0           235.0   \n",
       "4    -122.25     37.85                52.0       1627.0           280.0   \n",
       "\n",
       "   population  households  median_income  median_house_value ocean_proximity  \n",
       "0       322.0       126.0         8.3252           13.022766        NEAR BAY  \n",
       "1      2401.0      1138.0         8.3014           12.789687        NEAR BAY  \n",
       "2       496.0       177.0         7.2574           12.771673        NEAR BAY  \n",
       "3       558.0       219.0         5.6431           12.740520        NEAR BAY  \n",
       "4       565.0       259.0         3.8462           12.743154        NEAR BAY  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "afdb54e8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f95072bf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1c57fc7a",
   "metadata": {},
   "source": [
    "Do train/validation/test split with 60%/20%/20% distribution. \n",
    "\n",
    "Use the train_test_split function and set the random_state parameter to 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4a19f474",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data.drop(\"median_house_value\",axis=1)\n",
    "y = data[\"median_house_value\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "36467d05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((16512, 9), (16512,), (4128, 9), (4128,))"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train_full, X_test, y_train_full, y_test = train_test_split(X, y, test_size=0.2, random_state=1)\n",
    "X_train_full.shape, y_train_full.shape, X_test.shape, y_test.shape "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0266cf9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((12384, 9), (12384,), (4128, 9), (4128,))"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train, X_val, y_train, y_val = train_test_split(X_train_full, y_train_full, test_size=0.25, random_state=1)\n",
    "X_train.shape, y_train.shape, X_val.shape, y_val.shape "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fbd92ed4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3cc40fac",
   "metadata": {},
   "source": [
    "#### Use DictVectorizer to turn the dataframe into matrices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ca29cbc9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction import DictVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ac9eefd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_cols = X.columns.values\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "db3286ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DictVectorizer to convert Train, Validation and Test dataframes into matrices\n",
    "dv = DictVectorizer(sparse=False)\n",
    "\n",
    "train_dict = X_train[x_cols].to_dict(orient='records')\n",
    "Xtrain = dv.fit_transform(train_dict)\n",
    "\n",
    "val_dict = X_val[x_cols].to_dict(orient='records')\n",
    "Xval = dv.transform(val_dict)\n",
    "\n",
    "test_dict = X_test[x_cols].to_dict(orient='records')\n",
    "Xtest = dv.transform(test_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "088f8599",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['households',\n",
       " 'housing_median_age',\n",
       " 'latitude',\n",
       " 'longitude',\n",
       " 'median_income',\n",
       " 'ocean_proximity=<1H OCEAN',\n",
       " 'ocean_proximity=INLAND',\n",
       " 'ocean_proximity=ISLAND',\n",
       " 'ocean_proximity=NEAR BAY',\n",
       " 'ocean_proximity=NEAR OCEAN',\n",
       " 'population',\n",
       " 'total_bedrooms',\n",
       " 'total_rooms']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_cols_dv = list(dv.get_feature_names_out())\n",
    "x_cols_dv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ce2e4e3d",
   "metadata": {},
   "outputs": [],
   "source": [
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b2d3d090",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e089b520",
   "metadata": {},
   "source": [
    "Question 1\n",
    "\n",
    "Let's train a decision tree regressor to predict the median_house_value variable.\n",
    "\n",
    "    Train a model with max_depth=1.\n",
    "\n",
    "Which feature is used for splitting the data?\n",
    "\n",
    "- **ocean_proximity=INLAND**\n",
    "- total_rooms\n",
    "- latitude\n",
    "- population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "352783d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import export_text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "57e9a0aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree:\n",
      "|--- ocean_proximity=INLAND <= 0.50\n",
      "|   |--- value: [12.31]\n",
      "|--- ocean_proximity=INLAND >  0.50\n",
      "|   |--- value: [11.61]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Decision Tree Regression Model\n",
    "dt_reg = DecisionTreeRegressor(max_depth=1)\n",
    "model = dt_reg.fit(Xtrain, y_train)\n",
    "\n",
    "print(\"Decision Tree:\")\n",
    "print(export_text(model, feature_names = list(dv.get_feature_names_out())))\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b221ae0f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96e52017",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3d70ea21",
   "metadata": {},
   "source": [
    "Question 2\n",
    "\n",
    "Train a random forest model with these parameters:\n",
    "\n",
    "    n_estimators=10\n",
    "    random_state=1\n",
    "    n_jobs=-1 (optional - to make training faster)\n",
    "\n",
    "What's the RMSE of this model on validation?\n",
    "\n",
    "- 0.05\n",
    "- **0.25**\n",
    "- 0.55\n",
    "- 0.85"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "38a57e6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f3b9881a",
   "metadata": {},
   "outputs": [],
   "source": [
    "estimators = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ee5d461b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forest Regressor\n",
      "Training RMSE:  0.11\n",
      "Validation RMSE:  0.25\n"
     ]
    }
   ],
   "source": [
    "rf_reg = RandomForestRegressor(n_estimators=estimators, random_state=1, n_jobs=-1)\n",
    "model = rf_reg.fit(Xtrain, y_train)\n",
    "\n",
    "y_train_pred = model.predict(Xtrain)\n",
    "\n",
    "print(\"Random Forest Regressor\")\n",
    "print(\"Training RMSE: \", np.round(np.sqrt(mean_squared_error(y_train, y_train_pred)),2))\n",
    "\n",
    "y_val_pred = model.predict(Xval)\n",
    "print(\"Validation RMSE: \", np.round(np.sqrt(mean_squared_error(y_val, y_val_pred)),2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35c7aaaa",
   "metadata": {},
   "outputs": [],
   "source": [
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7a41124",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8d34e7a2",
   "metadata": {},
   "source": [
    "Question 3\n",
    "\n",
    "Now let's experiment with the n_estimators parameter\n",
    "\n",
    "    Try different values of this parameter from 10 to 200 with step 10.\n",
    "    Set random_state to 1.\n",
    "    Evaluate the model on the validation dataset.\n",
    "\n",
    "After which value of n_estimators does RMSE stop improving?\n",
    "\n",
    "- 10\n",
    "- 55\n",
    "- **75**\n",
    "- 150"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a61b4e7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "estimators = np.arange(10,210,10)\n",
    "scores = []\n",
    "\n",
    "for n in estimators:\n",
    "    rf_reg = RandomForestRegressor(n_estimators=n, random_state=1, n_jobs=-1)\n",
    "    \n",
    "    model = rf_reg.fit(Xtrain, y_train)\n",
    "\n",
    "    y_train_pred = model.predict(Xtrain)\n",
    "    \n",
    "    y_val_pred = model.predict(Xval)\n",
    "    \n",
    "    scores.append(np.sqrt(mean_squared_error(y_val, y_val_pred)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e5e0a82f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\anaconda3\\envs\\ml-zoomcamp\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,7))\n",
    "\n",
    "sns.lineplot(estimators, scores, )\n",
    "plt.xlabel(\"No. of Estimators\")\n",
    "plt.ylabel(\"RMSE Scores\")\n",
    "plt.title(\"Random Forest RMSE Scores vs No. of Estimators\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4e76b796",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "110"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "estimators[np.argmin(scores)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3aabf81b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "765b637b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "779476d5",
   "metadata": {},
   "source": [
    "Question 4\n",
    "\n",
    "Let's select the best max_depth:\n",
    "\n",
    "    Try different values of max_depth: [10, 15, 20, 25]\n",
    "    For each of these values, try different values of n_estimators from 10 till 200 (with step 10)\n",
    "    Fix the random seed: random_state=1\n",
    "\n",
    "What's the best max_depth:\n",
    "\n",
    "- 10\n",
    "- 15\n",
    "- 20\n",
    "- **25**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5f95b8b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "depths =  [10, 15, 20, 25]\n",
    "estimators = np.arange(10,210,10)\n",
    "scores = []\n",
    "\n",
    "for d in depths:\n",
    "    for n in estimators:\n",
    "        rf_reg = RandomForestRegressor(n_estimators=n, random_state=1, n_jobs=-1, max_depth=d)\n",
    "\n",
    "        model = rf_reg.fit(Xtrain, y_train)\n",
    "\n",
    "        y_train_pred = model.predict(Xtrain)\n",
    "\n",
    "        y_val_pred = model.predict(Xval)\n",
    "\n",
    "        score = np.sqrt(mean_squared_error(y_val, y_val_pred))\n",
    "        \n",
    "        scores.append({'max_depth':d,'n_estimators':n,'rmse':score})\n",
    "    \n",
    "df_scores = pd.DataFrame(scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c24fab18",
   "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>max_depth</th>\n",
       "      <th>n_estimators</th>\n",
       "      <th>rmse</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>0.255042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>0.252784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10</td>\n",
       "      <td>30</td>\n",
       "      <td>0.251647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>40</td>\n",
       "      <td>0.251062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>50</td>\n",
       "      <td>0.250192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>25</td>\n",
       "      <td>160</td>\n",
       "      <td>0.231484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>25</td>\n",
       "      <td>170</td>\n",
       "      <td>0.231440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>25</td>\n",
       "      <td>180</td>\n",
       "      <td>0.231598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>25</td>\n",
       "      <td>190</td>\n",
       "      <td>0.231603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>25</td>\n",
       "      <td>200</td>\n",
       "      <td>0.231492</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>80 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    max_depth  n_estimators      rmse\n",
       "0          10            10  0.255042\n",
       "1          10            20  0.252784\n",
       "2          10            30  0.251647\n",
       "3          10            40  0.251062\n",
       "4          10            50  0.250192\n",
       "..        ...           ...       ...\n",
       "75         25           160  0.231484\n",
       "76         25           170  0.231440\n",
       "77         25           180  0.231598\n",
       "78         25           190  0.231603\n",
       "79         25           200  0.231492\n",
       "\n",
       "[80 rows x 3 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "1916ffdb",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x4000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,40))\n",
    "\n",
    "sns.lineplot(x=\"max_depth\", y=\"rmse\", hue=\"n_estimators\", data=df_scores, palette=\"tab20c\")\n",
    "plt.xlabel(\"Max Depth\")\n",
    "plt.ylabel(\"RMSE Scores\")\n",
    "plt.title(\"Random Forest RMSE Scores vs Max Depth\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a8ca63ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "max_depth       10.000000\n",
       "n_estimators    10.000000\n",
       "rmse             0.231255\n",
       "dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_scores.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a436918f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "max_depth        25.000000\n",
       "n_estimators    110.000000\n",
       "rmse              0.231255\n",
       "Name: 70, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_scores.loc[df_scores.rmse.argmin()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aff90fc0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37c83f70",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "bb311933",
   "metadata": {},
   "source": [
    "Question 5\n",
    "\n",
    "We can extract feature importance information from tree-based models.\n",
    "\n",
    "At each step of the decision tree learning algorith, it finds the best split.\n",
    "When doint it, we can calculate \"gain\" - the reduction in impurity before and after the split. \n",
    "This gain is quite useful in understanding what are the imporatant features for tree-based models.\n",
    "\n",
    "In Scikit-Learn, tree-based models contain this information in the feature_importances_ field.\n",
    "\n",
    "For this homework question, we'll find the most important feature:\n",
    "\n",
    "    Train the model with these parametes:\n",
    "        n_estimators=10,\n",
    "        max_depth=20,\n",
    "        random_state=1,\n",
    "        n_jobs=-1 (optional)\n",
    "    Get the feature importance information from this model\n",
    "\n",
    "What's the most important feature?\n",
    "\n",
    "- total_rooms\n",
    "- **median_income**\n",
    "- total_bedrooms\n",
    "- longitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "691a1aeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "rf_reg = RandomForestRegressor(max_depth = 20, n_estimators=10,n_jobs=-1,random_state=1)\n",
    "model = rf_reg.fit(Xtrain,y_train)\n",
    "\n",
    "importances = pd.Series(model.feature_importances_,index=dv.get_feature_names_out())\n",
    "importances.sort_values(ascending=False,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "0aadea7d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\anaconda3\\envs\\ml-zoomcamp\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "plt.xticks(rotation=90)\n",
    "sns.barplot(importances.index, importances.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8159bf6a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47445ad9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3e0f7c89",
   "metadata": {},
   "source": [
    "Question 6\n",
    "\n",
    "Now let's train an XGBoost model! For this question, we'll tune the eta parameter:\n",
    "\n",
    "    Install XGBoost\n",
    "    Create DMatrix for train and validation\n",
    "    Create a watchlist\n",
    "    Train a model with these parameters for 100 rounds:\n",
    "\n",
    "xgb_params = {\n",
    "    'eta': 0.3, \n",
    "    'max_depth': 6,\n",
    "    'min_child_weight': 1,\n",
    "    \n",
    "    'objective': 'reg:squarederror',\n",
    "    'nthread': 8,\n",
    "    \n",
    "    'seed': 1,\n",
    "    'verbosity': 1,\n",
    "}\n",
    "\n",
    "Now change eta first to 0.1 and then to 0.01\n",
    "\n",
    "Which eta leads to the best RMSE score on the validation dataset?\n",
    "\n",
    "- **0.3**\n",
    "- 0.1\n",
    "- Both gives same"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "c65fba0e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: xgboost in c:\\anaconda3\\envs\\ml-zoomcamp\\lib\\site-packages (1.6.2)\n",
      "Requirement already satisfied: numpy in c:\\anaconda3\\envs\\ml-zoomcamp\\lib\\site-packages (from xgboost) (1.22.4)\n",
      "Requirement already satisfied: scipy in c:\\anaconda3\\envs\\ml-zoomcamp\\lib\\site-packages (from xgboost) (1.7.3)\n"
     ]
    }
   ],
   "source": [
    "!pip install xgboost "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e14f1662",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xgboost as xgb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "1dc2e5b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['households',\n",
       " 'housing_median_age',\n",
       " 'latitude',\n",
       " 'longitude',\n",
       " 'median_income',\n",
       " 'ocean_proximity=<1H OCEAN',\n",
       " 'ocean_proximity=INLAND',\n",
       " 'ocean_proximity=ISLAND',\n",
       " 'ocean_proximity=NEAR BAY',\n",
       " 'ocean_proximity=NEAR OCEAN',\n",
       " 'population',\n",
       " 'total_bedrooms',\n",
       " 'total_rooms']"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = list(dv.get_feature_names_out())\n",
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "75806034",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['households',\n",
       " 'housing_median_age',\n",
       " 'latitude',\n",
       " 'longitude',\n",
       " 'median_income',\n",
       " 'ocean_proximity=less1H OCEAN',\n",
       " 'ocean_proximity=INLAND',\n",
       " 'ocean_proximity=ISLAND',\n",
       " 'ocean_proximity=NEAR BAY',\n",
       " 'ocean_proximity=NEAR OCEAN',\n",
       " 'population',\n",
       " 'total_bedrooms',\n",
       " 'total_rooms']"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = [feature.replace('<','less') for feature in features]\n",
    "features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd035862",
   "metadata": {},
   "source": [
    "#### Create DMatrix for train and validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "0bf170a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "dtrain = xgb.DMatrix(Xtrain, label=y_train, feature_names=features)\n",
    "dval = xgb.DMatrix(Xval, label=y_val, feature_names=features)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8413268",
   "metadata": {},
   "source": [
    "#### Create a watchlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "a267394c",
   "metadata": {},
   "outputs": [],
   "source": [
    "watch_list = [(dtrain,'train'),(dval,'val')] "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e076c31",
   "metadata": {},
   "source": [
    "#### Train model with eta = [0.3,0.1,0.01]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "7b1e7e09",
   "metadata": {},
   "outputs": [],
   "source": [
    "eta_values = [0.3,0.1,0.01]\n",
    "scores = pd.DataFrame()\n",
    "for eta in eta_values:\n",
    "    xgb_params = {\n",
    "                    'eta': eta, \n",
    "                    'max_depth': 6,\n",
    "                    'min_child_weight': 1,\n",
    "\n",
    "                    'objective': 'reg:squarederror',\n",
    "                    'nthread': 8,\n",
    "\n",
    "                    'seed': 1,\n",
    "                    'verbosity': 1,\n",
    "                }\n",
    "\n",
    "    evals_result = {}\n",
    "    \n",
    "    \n",
    "    model = xgb.train(xgb_params,\n",
    "                      dtrain=dtrain, \n",
    "                      num_boost_round=100, \n",
    "                      evals_result=evals_result,\n",
    "                      verbose_eval=False,\n",
    "                      evals=watch_list)\n",
    "    \n",
    "    df_scores = pd.DataFrame([evals_result['train']['rmse'],evals_result['val']['rmse']]).T\n",
    "    df_scores.columns = ['train_rmse','val_rmse']\n",
    "    df_scores['eta'] = eta \n",
    "    scores = pd.concat([scores,df_scores])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "21cd9779",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eta</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.01</th>\n",
       "      <td>100.0</td>\n",
       "      <td>7.294183</td>\n",
       "      <td>2.102219</td>\n",
       "      <td>4.264961</td>\n",
       "      <td>5.461396</td>\n",
       "      <td>6.996746</td>\n",
       "      <td>8.966232</td>\n",
       "      <td>11.492254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.10</th>\n",
       "      <td>100.0</td>\n",
       "      <td>1.195462</td>\n",
       "      <td>2.105760</td>\n",
       "      <td>0.230542</td>\n",
       "      <td>0.235186</td>\n",
       "      <td>0.254273</td>\n",
       "      <td>0.826368</td>\n",
       "      <td>10.449375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.30</th>\n",
       "      <td>100.0</td>\n",
       "      <td>0.480036</td>\n",
       "      <td>1.065971</td>\n",
       "      <td>0.225785</td>\n",
       "      <td>0.227672</td>\n",
       "      <td>0.231148</td>\n",
       "      <td>0.241359</td>\n",
       "      <td>8.132449</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      count      mean       std       min       25%       50%       75%  \\\n",
       "eta                                                                       \n",
       "0.01  100.0  7.294183  2.102219  4.264961  5.461396  6.996746  8.966232   \n",
       "0.10  100.0  1.195462  2.105760  0.230542  0.235186  0.254273  0.826368   \n",
       "0.30  100.0  0.480036  1.065971  0.225785  0.227672  0.231148  0.241359   \n",
       "\n",
       "            max  \n",
       "eta              \n",
       "0.01  11.492254  \n",
       "0.10  10.449375  \n",
       "0.30   8.132449  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores.groupby('eta').val_rmse.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "9c1fc91c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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>train_rmse</th>\n",
       "      <th>val_rmse</th>\n",
       "      <th>eta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8.127330</td>\n",
       "      <td>8.132449</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.695860</td>\n",
       "      <td>5.700702</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.995396</td>\n",
       "      <td>4.000411</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.807121</td>\n",
       "      <td>2.810786</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.978336</td>\n",
       "      <td>1.981749</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   train_rmse  val_rmse  eta\n",
       "0    8.127330  8.132449  0.3\n",
       "1    5.695860  5.700702  0.3\n",
       "2    3.995396  4.000411  0.3\n",
       "3    2.807121  2.810786  0.3\n",
       "4    1.978336  1.981749  0.3"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c0e29be1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "        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>val_rmse</th>\n",
       "      <th>eta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>0.225785</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>0.225823</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>0.225889</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>0.225949</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>0.225975</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11.040215</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.151528</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11.263970</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11.377531</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11.492254</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>300 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     val_rmse   eta\n",
       "85   0.225785  0.30\n",
       "86   0.225823  0.30\n",
       "83   0.225889  0.30\n",
       "82   0.225949  0.30\n",
       "84   0.225975  0.30\n",
       "..        ...   ...\n",
       "4   11.040215  0.01\n",
       "3   11.151528  0.01\n",
       "2   11.263970  0.01\n",
       "1   11.377531  0.01\n",
       "0   11.492254  0.01\n",
       "\n",
       "[300 rows x 2 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores[[\"val_rmse\", \"eta\"]].sort_values(by=\"val_rmse\",ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "888b311e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "train_rmse    0.141663\n",
       "val_rmse      0.225785\n",
       "eta           0.300000\n",
       "Name: 85, dtype: float64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores.iloc[scores.val_rmse.argmin()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "1b42e41b",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Train RMSE Vs No.of Rounds\")\n",
    "plt.xlabel(\"No. of XGBoost Rounds \")\n",
    "plt.ylabel(\"Train RMSE\")\n",
    "sns.lineplot(x=scores.index.values, y=scores.train_rmse.values, data=scores, hue=scores.eta.values, palette='tab20')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f4002143",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Validation RMSE Vs No.of Rounds\")\n",
    "plt.xlabel(\"No. of XGBoost Rounds \")\n",
    "plt.ylabel(\"Validation RMSE\")\n",
    "sns.lineplot(x=scores.index.values ,y=scores.val_rmse.values, hue=scores.eta.values, palette='tab20')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8cd6d846",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e493081c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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