{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7c5ba4fe",
   "metadata": {},
   "source": [
    "<a name='0'></a>\n",
    "# Support Vector Machines (SVM) - Intro and SVM for Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a262086",
   "metadata": {},
   "source": [
    "Support Vector Machines are the type of supervised learning algorithms used for regression, classification and detecting outliers. SVMs are remarkably one of the powerful models in classical machine learning suited for handling complex and high dimensional datasets. \n",
    "\n",
    "With SVM supporting different kernels (linear, polynomial, Radial Basis Function(rbf), and sigmoid), SVM can tackle different kinds of datasets, both linear and non linear. \n",
    "\n",
    "While the maths behind the SVMs are beyond the scope of this notebook, here is the idea behind SVMs:\n",
    "\n",
    "*The way SVM works can be compared to a street with a boundary line. During SVM training, SMV draws the large margin or decision boundary between classes based on the importance of each training data point. The training data points that are inside the decision boundary are called support vectors and hence the name.*\n",
    "\n",
    "![SVM](../../../../images/ml-fundamentals/1200px-Kernel_Machine.svg.png)\n",
    "\n",
    "SMVs are widely used for classification. But to motivate that, let's start with regression. For the purpose of examining how powerful this algorithm is, we will use the same dataset that we used in linear regression notebook, and hopefully the difference in performance will be notable. "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "ae5e8372",
   "metadata": {},
   "source": [
    "## Contents\n",
    "\n",
    "* [1 - Imports](#1)\n",
    "* [2 - Loading the data](#2)\n",
    "* [3 - Exploratory Analysis](#3)\n",
    "* [4 - Preprocessing the data](#4)\n",
    "* [5 - Training Support Vector Regressor](#5)\n",
    "* [6 - Evaluating Support Vector Regressor](#6)\n",
    "* [7 - Improving Support Vector Regressor](#7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99058d12",
   "metadata": {},
   "source": [
    "<a name='1'></a>\n",
    "## 1 - Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "df278c5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import urllib.request\n",
    "import sklearn\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35699c38",
   "metadata": {},
   "source": [
    "<a name='2'></a>\n",
    "\n",
    "## 2 - Loading the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6d848e37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cal_data = pd.read_csv(\"../../assets/data/housing.csv\")\n",
    "cal_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c1fc45c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20640"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(cal_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c492fd93",
   "metadata": {},
   "source": [
    "## 3 - Exploratory Analysis\n",
    "\n",
    "This is going to be a quick glance through the dataset. The full exploratory data analysis was done in the linear regression notebook[ADD LINK]. Before anything, let's split the data into training and test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "98d74144",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The size of training data is: 18576 \n",
      "The size of testing data is: 2064\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "train_data, test_data = train_test_split(cal_data, test_size=0.1,random_state=20)\n",
    "\n",
    "print('The size of training data is: {} \\nThe size of testing data is: {}'.format(len(train_data), len(test_data)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0314e577",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        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>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",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>longitude</th>\n",
       "      <td>18576.0</td>\n",
       "      <td>-119.567530</td>\n",
       "      <td>2.000581</td>\n",
       "      <td>-124.3500</td>\n",
       "      <td>-121.7900</td>\n",
       "      <td>-118.4900</td>\n",
       "      <td>-118.010000</td>\n",
       "      <td>-114.4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>latitude</th>\n",
       "      <td>18576.0</td>\n",
       "      <td>35.630217</td>\n",
       "      <td>2.133260</td>\n",
       "      <td>32.5400</td>\n",
       "      <td>33.9300</td>\n",
       "      <td>34.2600</td>\n",
       "      <td>37.710000</td>\n",
       "      <td>41.9500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>housing_median_age</th>\n",
       "      <td>18576.0</td>\n",
       "      <td>28.661068</td>\n",
       "      <td>12.604039</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>18.0000</td>\n",
       "      <td>29.0000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>52.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_rooms</th>\n",
       "      <td>18576.0</td>\n",
       "      <td>2631.567453</td>\n",
       "      <td>2169.467450</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>1445.0000</td>\n",
       "      <td>2127.0000</td>\n",
       "      <td>3149.000000</td>\n",
       "      <td>39320.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_bedrooms</th>\n",
       "      <td>18390.0</td>\n",
       "      <td>537.344698</td>\n",
       "      <td>417.672864</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>295.0000</td>\n",
       "      <td>435.0000</td>\n",
       "      <td>648.000000</td>\n",
       "      <td>6445.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population</th>\n",
       "      <td>18576.0</td>\n",
       "      <td>1422.408376</td>\n",
       "      <td>1105.486111</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>785.7500</td>\n",
       "      <td>1166.0000</td>\n",
       "      <td>1725.000000</td>\n",
       "      <td>28566.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>households</th>\n",
       "      <td>18576.0</td>\n",
       "      <td>499.277078</td>\n",
       "      <td>379.473497</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>279.0000</td>\n",
       "      <td>410.0000</td>\n",
       "      <td>606.000000</td>\n",
       "      <td>6082.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median_income</th>\n",
       "      <td>18576.0</td>\n",
       "      <td>3.870053</td>\n",
       "      <td>1.900225</td>\n",
       "      <td>0.4999</td>\n",
       "      <td>2.5643</td>\n",
       "      <td>3.5341</td>\n",
       "      <td>4.742725</td>\n",
       "      <td>15.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median_house_value</th>\n",
       "      <td>18576.0</td>\n",
       "      <td>206881.011305</td>\n",
       "      <td>115237.605962</td>\n",
       "      <td>14999.0000</td>\n",
       "      <td>120000.0000</td>\n",
       "      <td>179800.0000</td>\n",
       "      <td>264700.000000</td>\n",
       "      <td>500001.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      count           mean            std         min  \\\n",
       "longitude           18576.0    -119.567530       2.000581   -124.3500   \n",
       "latitude            18576.0      35.630217       2.133260     32.5400   \n",
       "housing_median_age  18576.0      28.661068      12.604039      1.0000   \n",
       "total_rooms         18576.0    2631.567453    2169.467450      2.0000   \n",
       "total_bedrooms      18390.0     537.344698     417.672864      1.0000   \n",
       "population          18576.0    1422.408376    1105.486111      3.0000   \n",
       "households          18576.0     499.277078     379.473497      1.0000   \n",
       "median_income       18576.0       3.870053       1.900225      0.4999   \n",
       "median_house_value  18576.0  206881.011305  115237.605962  14999.0000   \n",
       "\n",
       "                            25%          50%            75%          max  \n",
       "longitude             -121.7900    -118.4900    -118.010000    -114.4900  \n",
       "latitude                33.9300      34.2600      37.710000      41.9500  \n",
       "housing_median_age      18.0000      29.0000      37.000000      52.0000  \n",
       "total_rooms           1445.0000    2127.0000    3149.000000   39320.0000  \n",
       "total_bedrooms         295.0000     435.0000     648.000000    6445.0000  \n",
       "population             785.7500    1166.0000    1725.000000   28566.0000  \n",
       "households             279.0000     410.0000     606.000000    6082.0000  \n",
       "median_income            2.5643       3.5341       4.742725      15.0001  \n",
       "median_house_value  120000.0000  179800.0000  264700.000000  500001.0000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Checking statistics\n",
    "\n",
    "train_data.describe().transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d6c859d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "longitude               0\n",
       "latitude                0\n",
       "housing_median_age      0\n",
       "total_rooms             0\n",
       "total_bedrooms        186\n",
       "population              0\n",
       "households              0\n",
       "median_income           0\n",
       "median_house_value      0\n",
       "ocean_proximity         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Checking missing values\n",
    "\n",
    "train_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f52edb8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<1H OCEAN     8231\n",
       "INLAND        5896\n",
       "NEAR OCEAN    2384\n",
       "NEAR BAY      2061\n",
       "ISLAND           4\n",
       "Name: ocean_proximity, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking Values in the Categorical Feature(s)\n",
    "\n",
    "train_data['ocean_proximity'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a5d91ea5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='ocean_proximity', ylabel='count'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data=train_data, x='ocean_proximity')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2339e7e",
   "metadata": {},
   "source": [
    "Total bedroom is the only feature having missing values. Here is its distribution. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0bfe514d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: ylabel='Frequency'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_data['total_bedrooms'].plot(kind='hist')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4968843f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='longitude', ylabel='latitude'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting geographical features\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "\n",
    "sns.scatterplot(data = train_data, x='longitude', y='latitude', hue='ocean_proximity', \n",
    "                size='median_house_value')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6733727",
   "metadata": {},
   "source": [
    "<a name='4'></a>\n",
    "\n",
    "## 4 - Data Preprocessing \n",
    "\n",
    "To do: \n",
    "* Handle missing values\n",
    "* Encode categorical features\n",
    "* Scale the features\n",
    "* Everything into pipeline\n",
    "   \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0f099aa6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Getting training input data and labels\n",
    "\n",
    "training_input_data = train_data.drop('median_house_value', axis=1)\n",
    "training_labels = train_data['median_house_value']\n",
    "\n",
    "# Numerical features \n",
    "\n",
    "num_feats = training_input_data.drop('ocean_proximity', axis=1)\n",
    "\n",
    "# Categorical features \n",
    "cat_feats = training_input_data[['ocean_proximity']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f0e64e53",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Handle missing values \n",
    "\n",
    "from sklearn.pipeline import Pipeline \n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "num_pipe = Pipeline([\n",
    "      ('imputer', SimpleImputer(strategy='mean')),\n",
    "      ('scaler', StandardScaler())\n",
    "\n",
    "    ])\n",
    "\n",
    "num_preprocessed = num_pipe.fit_transform(num_feats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c5ff26fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pipeline to combine the numerical pipeline and also encode categorical features \n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "\n",
    "# The transformer requires lists of features\n",
    "\n",
    "num_list = list(num_feats)\n",
    "cat_list = list(cat_feats)\n",
    "\n",
    "final_pipe = ColumnTransformer([\n",
    "    ('num', num_pipe, num_list),\n",
    "    ('cat', OneHotEncoder(), cat_list)\n",
    "])\n",
    "\n",
    "training_data_preprocessed = final_pipe.fit_transform(training_input_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f7c61f40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.67858615, -0.85796668,  0.97899282, ...,  0.        ,\n",
       "         0.        ,  1.        ],\n",
       "       [-0.93598814,  0.41242353,  0.18557502, ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [-1.45585107,  0.9187045 ,  0.02689146, ...,  0.        ,\n",
       "         0.        ,  1.        ],\n",
       "       ...,\n",
       "       [ 1.27342931, -1.32674535,  0.18557502, ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [ 0.64859406, -0.71733307,  0.97899282, ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [-1.44085502,  1.01246024,  1.37570172, ...,  0.        ,\n",
       "         1.        ,  0.        ]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training_data_preprocessed"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd496de6",
   "metadata": {},
   "source": [
    "<a name='5'></a>\n",
    "\n",
    "## 5 - Training Support Vector Regressor\n",
    "\n",
    "In regression, instead of separating the classes with decision boundary  like in classification, SVR fits the training data points on the boundary margin but keep them off. \n",
    "\n",
    "We can implement it quite easily with Scikit-Learn."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "869b31a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import LinearSVR, SVR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "92959113",
   "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>LinearSVR()</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\">LinearSVR</label><div class=\"sk-toggleable__content\"><pre>LinearSVR()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "LinearSVR()"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lin_svr = LinearSVR()\n",
    "lin_svr.fit(training_data_preprocessed, training_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b25ca83d",
   "metadata": {},
   "source": [
    "We can also use nonlinear SVM with a polynomial kernel function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "703253ed",
   "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>SVR(kernel=&#x27;poly&#x27;)</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\">SVR</label><div class=\"sk-toggleable__content\"><pre>SVR(kernel=&#x27;poly&#x27;)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "SVR(kernel='poly')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "poly_svr = SVR(kernel='poly')\n",
    "poly_svr.fit(training_data_preprocessed, training_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9afb9bde",
   "metadata": {},
   "source": [
    "<a name='6'></a>\n",
    "\n",
    "## 6 - Evaluating Support Vector Regressor\n",
    "\n",
    "Let us evaluate the two models we created on the training set before evaluating on the test set. This is a good practice. Since finding a good model can take many iterations of improvements, it's not advised to touch the test set until the model is good enough. Otherwise it would fail to make predictions on the new data. \n",
    "\n",
    "As always, we evaluate regression models with mean squarred error, but the commonly used one is root mean squarred error. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6dc728df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "215682.86713461558"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "predictions = lin_svr.predict(training_data_preprocessed)\n",
    "mse = mean_squared_error(training_labels, predictions)\n",
    "rmse = np.sqrt(mse)\n",
    "rmse"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e79c6472",
   "metadata": {},
   "source": [
    "That's too high error. Let's see how SVR with polynomial kernel will perform. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b69c9f89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "117513.38828582528"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions = poly_svr.predict(training_data_preprocessed)\n",
    "mse = mean_squared_error(training_labels, predictions)\n",
    "rmse = np.sqrt(mse)\n",
    "rmse"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbdf054d",
   "metadata": {},
   "source": [
    "It did well than the former. For now, we can try to improve this with Randomized Search where we can find the best parameters. Let's do that!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b43c8d44",
   "metadata": {},
   "source": [
    "<a name='7'></a>\n",
    "\n",
    "## 7 - Improving Support Vector Regressor\n",
    "\n",
    "Let use Randomized Search to improve the SVR model. Few notes about the parameters:\n",
    "\n",
    "* *Gamma(y)*: This is a regularization hyperparameter. When gamma is small, the model can underfit. It is too high, model can overfit. \n",
    "* *C*: It's same as gamma. It is a regularization hyperparameter. When C is low, there is much regularization. When C is high, there is low regularization. \n",
    "* *epsilon*: is used to control the width of the street."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fd298880",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 10 candidates, totalling 30 fits\n",
      "[CV] END .............C=1, degree=2, epsilon=0, gamma=0.0001; total time=  17.0s\n",
      "[CV] END .............C=1, degree=2, epsilon=0, gamma=0.0001; total time=  16.2s\n",
      "[CV] END .............C=1, degree=2, epsilon=0, gamma=0.0001; total time=  15.4s\n",
      "[CV] END ................C=1, degree=2, epsilon=0, gamma=0.1; total time=  15.1s\n",
      "[CV] END ................C=1, degree=2, epsilon=0, gamma=0.1; total time=  15.2s\n",
      "[CV] END ................C=1, degree=2, epsilon=0, gamma=0.1; total time=  15.1s\n",
      "[CV] END ................C=1, degree=5, epsilon=0, gamma=0.1; total time=  15.4s\n",
      "[CV] END ................C=1, degree=5, epsilon=0, gamma=0.1; total time=  16.7s\n",
      "[CV] END ................C=1, degree=5, epsilon=0, gamma=0.1; total time=  14.8s\n",
      "[CV] END ........C=1000, degree=5, epsilon=0.5, gamma=0.0001; total time=  15.1s\n",
      "[CV] END ........C=1000, degree=5, epsilon=0.5, gamma=0.0001; total time=  15.3s\n",
      "[CV] END ........C=1000, degree=5, epsilon=0.5, gamma=0.0001; total time=  16.9s\n",
      "[CV] END .............C=1000, degree=5, epsilon=0, gamma=0.1; total time=  17.8s\n",
      "[CV] END .............C=1000, degree=5, epsilon=0, gamma=0.1; total time=  20.4s\n",
      "[CV] END .............C=1000, degree=5, epsilon=0, gamma=0.1; total time=  18.1s\n",
      "[CV] END ...........C=1000, degree=2, epsilon=0.5, gamma=0.1; total time=  20.8s\n",
      "[CV] END ...........C=1000, degree=2, epsilon=0.5, gamma=0.1; total time=  23.3s\n",
      "[CV] END ...........C=1000, degree=2, epsilon=0.5, gamma=0.1; total time=  22.2s\n",
      "[CV] END ..........C=1000, degree=2, epsilon=0, gamma=0.0001; total time=  20.6s\n",
      "[CV] END ..........C=1000, degree=2, epsilon=0, gamma=0.0001; total time=  20.1s\n",
      "[CV] END ..........C=1000, degree=2, epsilon=0, gamma=0.0001; total time=  20.3s\n",
      "[CV] END .............C=1000, degree=2, epsilon=0, gamma=0.1; total time=  19.0s\n",
      "[CV] END .............C=1000, degree=2, epsilon=0, gamma=0.1; total time=  18.9s\n",
      "[CV] END .............C=1000, degree=2, epsilon=0, gamma=0.1; total time=  19.7s\n",
      "[CV] END ...........C=1, degree=2, epsilon=0.5, gamma=0.0001; total time=  23.5s\n",
      "[CV] END ...........C=1, degree=2, epsilon=0.5, gamma=0.0001; total time=  27.7s\n",
      "[CV] END ...........C=1, degree=2, epsilon=0.5, gamma=0.0001; total time=  17.9s\n",
      "[CV] END ...........C=1000, degree=5, epsilon=0.5, gamma=0.1; total time=  16.7s\n",
      "[CV] END ...........C=1000, degree=5, epsilon=0.5, gamma=0.1; total time=  16.7s\n",
      "[CV] END ...........C=1000, degree=5, epsilon=0.5, gamma=0.1; total time=  15.2s\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {color: black;background-color: white;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 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-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 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-3 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-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 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-3 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-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 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-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 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-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 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-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomizedSearchCV(cv=3, estimator=SVR(),\n",
       "                   param_distributions={&#x27;C&#x27;: [1, 1000], &#x27;degree&#x27;: [2, 5],\n",
       "                                        &#x27;epsilon&#x27;: [0, 0.5],\n",
       "                                        &#x27;gamma&#x27;: [0.0001, 0.1]},\n",
       "                   random_state=42, verbose=2)</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-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomizedSearchCV</label><div class=\"sk-toggleable__content\"><pre>RandomizedSearchCV(cv=3, estimator=SVR(),\n",
       "                   param_distributions={&#x27;C&#x27;: [1, 1000], &#x27;degree&#x27;: [2, 5],\n",
       "                                        &#x27;epsilon&#x27;: [0, 0.5],\n",
       "                                        &#x27;gamma&#x27;: [0.0001, 0.1]},\n",
       "                   random_state=42, verbose=2)</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-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: SVR</label><div class=\"sk-toggleable__content\"><pre>SVR()</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-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SVR</label><div class=\"sk-toggleable__content\"><pre>SVR()</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "RandomizedSearchCV(cv=3, estimator=SVR(),\n",
       "                   param_distributions={'C': [1, 1000], 'degree': [2, 5],\n",
       "                                        'epsilon': [0, 0.5],\n",
       "                                        'gamma': [0.0001, 0.1]},\n",
       "                   random_state=42, verbose=2)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "\n",
    "\n",
    "params = {'gamma':[0.0001, 0.1],'C':[1,1000], 'epsilon':[0,0.5], 'degree':[2,5]}\n",
    "\n",
    "rnd_search = RandomizedSearchCV(SVR(), params, n_iter=10, verbose=2, cv=3, random_state=42)\n",
    "\n",
    "rnd_search.fit(training_data_preprocessed, training_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8b4d8b0",
   "metadata": {},
   "source": [
    "We can now find the best parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "dcdbda1e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'gamma': 0.1, 'epsilon': 0, 'degree': 5, 'C': 1000}"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rnd_search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "29f91afe",
   "metadata": {},
   "outputs": [],
   "source": [
    "svr_rnd = rnd_search.best_estimator_.fit(training_data_preprocessed, training_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3821f51c",
   "metadata": {},
   "source": [
    "Now, let's evaluate it on the training set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6e249653",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68684.15262765526"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions = svr_rnd.predict(training_data_preprocessed)\n",
    "mse = mean_squared_error(training_labels, predictions)\n",
    "rmse = np.sqrt(mse)\n",
    "rmse"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2fc0d66",
   "metadata": {},
   "source": [
    "Wow, this is much bettter. We were able to improve reduce the root mean squarred error from `$117,513` to `$68,684`. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "352268fd",
   "metadata": {},
   "source": [
    "Now, we can evaluate the model on the test set. We will have to transform it the same way we transformed the training set for the prediction to be possible. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "562f2117",
   "metadata": {},
   "outputs": [],
   "source": [
    "test_input_data = test_data.drop('median_house_value', axis=1)\n",
    "test_labels = test_data['median_house_value']\n",
    "\n",
    "\n",
    "test_preprocessed = final_pipe.transform(test_input_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3ce32495",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68478.07737338323"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_pred = svr_rnd.predict(test_preprocessed)\n",
    "test_mse = mean_squared_error(test_labels,test_pred)\n",
    "\n",
    "test_rmse = np.sqrt(test_mse)\n",
    "test_rmse"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9086f648",
   "metadata": {},
   "source": [
    "That's is not really bad."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53988b69",
   "metadata": {},
   "source": [
    "This is the end of the notebook. It was a practical introduction to using Support Vector Machines for regression. In the next lab, we will take a further step, where we will do classification with SVM. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82fa2f57",
   "metadata": {},
   "source": [
    "## Acknowledgments\n",
    "\n",
    "Thanks to Jake VanderPlas for creating the open-source course [ Python Data Science Handbook ](https://github.com/jakevdp/PythonDataScienceHandbook). It inspires the majority of the content in this chapter."
   ]
  }
 ],
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