SVR.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SUPPORT VECTOR REGRESSION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\"\"\"Importing the modules\"\"\"\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>Unnamed: 0</th>\n",
       "      <th>crim</th>\n",
       "      <th>zn</th>\n",
       "      <th>indus</th>\n",
       "      <th>chas</th>\n",
       "      <th>nox</th>\n",
       "      <th>rm</th>\n",
       "      <th>age</th>\n",
       "      <th>dis</th>\n",
       "      <th>rad</th>\n",
       "      <th>tax</th>\n",
       "      <th>ptratio</th>\n",
       "      <th>black</th>\n",
       "      <th>lstat</th>\n",
       "      <th>medv</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.00632</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.0900</td>\n",
       "      <td>1</td>\n",
       "      <td>296</td>\n",
       "      <td>15.3</td>\n",
       "      <td>396.90</td>\n",
       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.02731</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2</td>\n",
       "      <td>242</td>\n",
       "      <td>17.8</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0.02729</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2</td>\n",
       "      <td>242</td>\n",
       "      <td>17.8</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>222</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>222</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>0.02985</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.430</td>\n",
       "      <td>58.7</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>222</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.12</td>\n",
       "      <td>5.21</td>\n",
       "      <td>28.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>0.08829</td>\n",
       "      <td>12.5</td>\n",
       "      <td>7.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0.524</td>\n",
       "      <td>6.012</td>\n",
       "      <td>66.6</td>\n",
       "      <td>5.5605</td>\n",
       "      <td>5</td>\n",
       "      <td>311</td>\n",
       "      <td>15.2</td>\n",
       "      <td>395.60</td>\n",
       "      <td>12.43</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>0.14455</td>\n",
       "      <td>12.5</td>\n",
       "      <td>7.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0.524</td>\n",
       "      <td>6.172</td>\n",
       "      <td>96.1</td>\n",
       "      <td>5.9505</td>\n",
       "      <td>5</td>\n",
       "      <td>311</td>\n",
       "      <td>15.2</td>\n",
       "      <td>396.90</td>\n",
       "      <td>19.15</td>\n",
       "      <td>27.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>0.21124</td>\n",
       "      <td>12.5</td>\n",
       "      <td>7.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0.524</td>\n",
       "      <td>5.631</td>\n",
       "      <td>100.0</td>\n",
       "      <td>6.0821</td>\n",
       "      <td>5</td>\n",
       "      <td>311</td>\n",
       "      <td>15.2</td>\n",
       "      <td>386.63</td>\n",
       "      <td>29.93</td>\n",
       "      <td>16.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>0.17004</td>\n",
       "      <td>12.5</td>\n",
       "      <td>7.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0.524</td>\n",
       "      <td>6.004</td>\n",
       "      <td>85.9</td>\n",
       "      <td>6.5921</td>\n",
       "      <td>5</td>\n",
       "      <td>311</td>\n",
       "      <td>15.2</td>\n",
       "      <td>386.71</td>\n",
       "      <td>17.10</td>\n",
       "      <td>18.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>0.22489</td>\n",
       "      <td>12.5</td>\n",
       "      <td>7.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0.524</td>\n",
       "      <td>6.377</td>\n",
       "      <td>94.3</td>\n",
       "      <td>6.3467</td>\n",
       "      <td>5</td>\n",
       "      <td>311</td>\n",
       "      <td>15.2</td>\n",
       "      <td>392.52</td>\n",
       "      <td>20.45</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>0.11747</td>\n",
       "      <td>12.5</td>\n",
       "      <td>7.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0.524</td>\n",
       "      <td>6.009</td>\n",
       "      <td>82.9</td>\n",
       "      <td>6.2267</td>\n",
       "      <td>5</td>\n",
       "      <td>311</td>\n",
       "      <td>15.2</td>\n",
       "      <td>396.90</td>\n",
       "      <td>13.27</td>\n",
       "      <td>18.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>0.09378</td>\n",
       "      <td>12.5</td>\n",
       "      <td>7.87</td>\n",
       "      <td>0</td>\n",
       "      <td>0.524</td>\n",
       "      <td>5.889</td>\n",
       "      <td>39.0</td>\n",
       "      <td>5.4509</td>\n",
       "      <td>5</td>\n",
       "      <td>311</td>\n",
       "      <td>15.2</td>\n",
       "      <td>390.50</td>\n",
       "      <td>15.71</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>0.62976</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.949</td>\n",
       "      <td>61.8</td>\n",
       "      <td>4.7075</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>8.26</td>\n",
       "      <td>20.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>0.63796</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.096</td>\n",
       "      <td>84.5</td>\n",
       "      <td>4.4619</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>380.02</td>\n",
       "      <td>10.26</td>\n",
       "      <td>18.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>0.62739</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.834</td>\n",
       "      <td>56.5</td>\n",
       "      <td>4.4986</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>395.62</td>\n",
       "      <td>8.47</td>\n",
       "      <td>19.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>1.05393</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.935</td>\n",
       "      <td>29.3</td>\n",
       "      <td>4.4986</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>386.85</td>\n",
       "      <td>6.58</td>\n",
       "      <td>23.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>0.78420</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.990</td>\n",
       "      <td>81.7</td>\n",
       "      <td>4.2579</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>386.75</td>\n",
       "      <td>14.67</td>\n",
       "      <td>17.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>0.80271</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.456</td>\n",
       "      <td>36.6</td>\n",
       "      <td>3.7965</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>288.99</td>\n",
       "      <td>11.69</td>\n",
       "      <td>20.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>0.72580</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.727</td>\n",
       "      <td>69.5</td>\n",
       "      <td>3.7965</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>390.95</td>\n",
       "      <td>11.28</td>\n",
       "      <td>18.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>1.25179</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.570</td>\n",
       "      <td>98.1</td>\n",
       "      <td>3.7979</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>376.57</td>\n",
       "      <td>21.02</td>\n",
       "      <td>13.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>0.85204</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.965</td>\n",
       "      <td>89.2</td>\n",
       "      <td>4.0123</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>392.53</td>\n",
       "      <td>13.83</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>1.23247</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.142</td>\n",
       "      <td>91.7</td>\n",
       "      <td>3.9769</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>18.72</td>\n",
       "      <td>15.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>0.98843</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.813</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4.0952</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>394.54</td>\n",
       "      <td>19.88</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>0.75026</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.924</td>\n",
       "      <td>94.1</td>\n",
       "      <td>4.3996</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>394.33</td>\n",
       "      <td>16.30</td>\n",
       "      <td>15.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>0.84054</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.599</td>\n",
       "      <td>85.7</td>\n",
       "      <td>4.4546</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>303.42</td>\n",
       "      <td>16.51</td>\n",
       "      <td>13.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>0.67191</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.813</td>\n",
       "      <td>90.3</td>\n",
       "      <td>4.6820</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>376.88</td>\n",
       "      <td>14.81</td>\n",
       "      <td>16.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>0.95577</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.047</td>\n",
       "      <td>88.8</td>\n",
       "      <td>4.4534</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>306.38</td>\n",
       "      <td>17.28</td>\n",
       "      <td>14.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>0.77299</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.495</td>\n",
       "      <td>94.4</td>\n",
       "      <td>4.4547</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>387.94</td>\n",
       "      <td>12.80</td>\n",
       "      <td>18.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>1.00245</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.674</td>\n",
       "      <td>87.3</td>\n",
       "      <td>4.2390</td>\n",
       "      <td>4</td>\n",
       "      <td>307</td>\n",
       "      <td>21.0</td>\n",
       "      <td>380.23</td>\n",
       "      <td>11.98</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0     crim    zn  indus  chas    nox     rm    age     dis  rad  \\\n",
       "0            1  0.00632  18.0   2.31     0  0.538  6.575   65.2  4.0900    1   \n",
       "1            2  0.02731   0.0   7.07     0  0.469  6.421   78.9  4.9671    2   \n",
       "2            3  0.02729   0.0   7.07     0  0.469  7.185   61.1  4.9671    2   \n",
       "3            4  0.03237   0.0   2.18     0  0.458  6.998   45.8  6.0622    3   \n",
       "4            5  0.06905   0.0   2.18     0  0.458  7.147   54.2  6.0622    3   \n",
       "5            6  0.02985   0.0   2.18     0  0.458  6.430   58.7  6.0622    3   \n",
       "6            7  0.08829  12.5   7.87     0  0.524  6.012   66.6  5.5605    5   \n",
       "7            8  0.14455  12.5   7.87     0  0.524  6.172   96.1  5.9505    5   \n",
       "8            9  0.21124  12.5   7.87     0  0.524  5.631  100.0  6.0821    5   \n",
       "9           10  0.17004  12.5   7.87     0  0.524  6.004   85.9  6.5921    5   \n",
       "10          11  0.22489  12.5   7.87     0  0.524  6.377   94.3  6.3467    5   \n",
       "11          12  0.11747  12.5   7.87     0  0.524  6.009   82.9  6.2267    5   \n",
       "12          13  0.09378  12.5   7.87     0  0.524  5.889   39.0  5.4509    5   \n",
       "13          14  0.62976   0.0   8.14     0  0.538  5.949   61.8  4.7075    4   \n",
       "14          15  0.63796   0.0   8.14     0  0.538  6.096   84.5  4.4619    4   \n",
       "15          16  0.62739   0.0   8.14     0  0.538  5.834   56.5  4.4986    4   \n",
       "16          17  1.05393   0.0   8.14     0  0.538  5.935   29.3  4.4986    4   \n",
       "17          18  0.78420   0.0   8.14     0  0.538  5.990   81.7  4.2579    4   \n",
       "18          19  0.80271   0.0   8.14     0  0.538  5.456   36.6  3.7965    4   \n",
       "19          20  0.72580   0.0   8.14     0  0.538  5.727   69.5  3.7965    4   \n",
       "20          21  1.25179   0.0   8.14     0  0.538  5.570   98.1  3.7979    4   \n",
       "21          22  0.85204   0.0   8.14     0  0.538  5.965   89.2  4.0123    4   \n",
       "22          23  1.23247   0.0   8.14     0  0.538  6.142   91.7  3.9769    4   \n",
       "23          24  0.98843   0.0   8.14     0  0.538  5.813  100.0  4.0952    4   \n",
       "24          25  0.75026   0.0   8.14     0  0.538  5.924   94.1  4.3996    4   \n",
       "25          26  0.84054   0.0   8.14     0  0.538  5.599   85.7  4.4546    4   \n",
       "26          27  0.67191   0.0   8.14     0  0.538  5.813   90.3  4.6820    4   \n",
       "27          28  0.95577   0.0   8.14     0  0.538  6.047   88.8  4.4534    4   \n",
       "28          29  0.77299   0.0   8.14     0  0.538  6.495   94.4  4.4547    4   \n",
       "29          30  1.00245   0.0   8.14     0  0.538  6.674   87.3  4.2390    4   \n",
       "\n",
       "    tax  ptratio   black  lstat  medv  \n",
       "0   296     15.3  396.90   4.98  24.0  \n",
       "1   242     17.8  396.90   9.14  21.6  \n",
       "2   242     17.8  392.83   4.03  34.7  \n",
       "3   222     18.7  394.63   2.94  33.4  \n",
       "4   222     18.7  396.90   5.33  36.2  \n",
       "5   222     18.7  394.12   5.21  28.7  \n",
       "6   311     15.2  395.60  12.43  22.9  \n",
       "7   311     15.2  396.90  19.15  27.1  \n",
       "8   311     15.2  386.63  29.93  16.5  \n",
       "9   311     15.2  386.71  17.10  18.9  \n",
       "10  311     15.2  392.52  20.45  15.0  \n",
       "11  311     15.2  396.90  13.27  18.9  \n",
       "12  311     15.2  390.50  15.71  21.7  \n",
       "13  307     21.0  396.90   8.26  20.4  \n",
       "14  307     21.0  380.02  10.26  18.2  \n",
       "15  307     21.0  395.62   8.47  19.9  \n",
       "16  307     21.0  386.85   6.58  23.1  \n",
       "17  307     21.0  386.75  14.67  17.5  \n",
       "18  307     21.0  288.99  11.69  20.2  \n",
       "19  307     21.0  390.95  11.28  18.2  \n",
       "20  307     21.0  376.57  21.02  13.6  \n",
       "21  307     21.0  392.53  13.83  19.6  \n",
       "22  307     21.0  396.90  18.72  15.2  \n",
       "23  307     21.0  394.54  19.88  14.5  \n",
       "24  307     21.0  394.33  16.30  15.6  \n",
       "25  307     21.0  303.42  16.51  13.9  \n",
       "26  307     21.0  376.88  14.81  16.6  \n",
       "27  307     21.0  306.38  17.28  14.8  \n",
       "28  307     21.0  387.94  12.80  18.4  \n",
       "29  307     21.0  380.23  11.98  21.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('Boston.csv')\n",
    "data.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0    0\n",
       "crim          0\n",
       "zn            0\n",
       "indus         0\n",
       "chas          0\n",
       "nox           0\n",
       "rm            0\n",
       "age           0\n",
       "dis           0\n",
       "rad           0\n",
       "tax           0\n",
       "ptratio       0\n",
       "black         0\n",
       "lstat         0\n",
       "medv          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"check for the null values in the data\"\"\"\n",
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Unnamed: 0</th>\n",
       "      <th>crim</th>\n",
       "      <th>zn</th>\n",
       "      <th>indus</th>\n",
       "      <th>chas</th>\n",
       "      <th>nox</th>\n",
       "      <th>rm</th>\n",
       "      <th>age</th>\n",
       "      <th>dis</th>\n",
       "      <th>rad</th>\n",
       "      <th>tax</th>\n",
       "      <th>ptratio</th>\n",
       "      <th>black</th>\n",
       "      <th>lstat</th>\n",
       "      <th>medv</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.407407</td>\n",
       "      <td>-0.103393</td>\n",
       "      <td>0.399439</td>\n",
       "      <td>-0.003759</td>\n",
       "      <td>0.398736</td>\n",
       "      <td>-0.079971</td>\n",
       "      <td>0.203784</td>\n",
       "      <td>-0.302211</td>\n",
       "      <td>0.686002</td>\n",
       "      <td>0.666626</td>\n",
       "      <td>0.291074</td>\n",
       "      <td>-0.295041</td>\n",
       "      <td>0.258465</td>\n",
       "      <td>-0.226604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>crim</th>\n",
       "      <td>0.407407</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.200469</td>\n",
       "      <td>0.406583</td>\n",
       "      <td>-0.055892</td>\n",
       "      <td>0.420972</td>\n",
       "      <td>-0.219247</td>\n",
       "      <td>0.352734</td>\n",
       "      <td>-0.379670</td>\n",
       "      <td>0.625505</td>\n",
       "      <td>0.582764</td>\n",
       "      <td>0.289946</td>\n",
       "      <td>-0.385064</td>\n",
       "      <td>0.455621</td>\n",
       "      <td>-0.388305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zn</th>\n",
       "      <td>-0.103393</td>\n",
       "      <td>-0.200469</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.533828</td>\n",
       "      <td>-0.042697</td>\n",
       "      <td>-0.516604</td>\n",
       "      <td>0.311991</td>\n",
       "      <td>-0.569537</td>\n",
       "      <td>0.664408</td>\n",
       "      <td>-0.311948</td>\n",
       "      <td>-0.314563</td>\n",
       "      <td>-0.391679</td>\n",
       "      <td>0.175520</td>\n",
       "      <td>-0.412995</td>\n",
       "      <td>0.360445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>indus</th>\n",
       "      <td>0.399439</td>\n",
       "      <td>0.406583</td>\n",
       "      <td>-0.533828</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.062938</td>\n",
       "      <td>0.763651</td>\n",
       "      <td>-0.391676</td>\n",
       "      <td>0.644779</td>\n",
       "      <td>-0.708027</td>\n",
       "      <td>0.595129</td>\n",
       "      <td>0.720760</td>\n",
       "      <td>0.383248</td>\n",
       "      <td>-0.356977</td>\n",
       "      <td>0.603800</td>\n",
       "      <td>-0.483725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chas</th>\n",
       "      <td>-0.003759</td>\n",
       "      <td>-0.055892</td>\n",
       "      <td>-0.042697</td>\n",
       "      <td>0.062938</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.091203</td>\n",
       "      <td>0.091251</td>\n",
       "      <td>0.086518</td>\n",
       "      <td>-0.099176</td>\n",
       "      <td>-0.007368</td>\n",
       "      <td>-0.035587</td>\n",
       "      <td>-0.121515</td>\n",
       "      <td>0.048788</td>\n",
       "      <td>-0.053929</td>\n",
       "      <td>0.175260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nox</th>\n",
       "      <td>0.398736</td>\n",
       "      <td>0.420972</td>\n",
       "      <td>-0.516604</td>\n",
       "      <td>0.763651</td>\n",
       "      <td>0.091203</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.302188</td>\n",
       "      <td>0.731470</td>\n",
       "      <td>-0.769230</td>\n",
       "      <td>0.611441</td>\n",
       "      <td>0.668023</td>\n",
       "      <td>0.188933</td>\n",
       "      <td>-0.380051</td>\n",
       "      <td>0.590879</td>\n",
       "      <td>-0.427321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rm</th>\n",
       "      <td>-0.079971</td>\n",
       "      <td>-0.219247</td>\n",
       "      <td>0.311991</td>\n",
       "      <td>-0.391676</td>\n",
       "      <td>0.091251</td>\n",
       "      <td>-0.302188</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.240265</td>\n",
       "      <td>0.205246</td>\n",
       "      <td>-0.209847</td>\n",
       "      <td>-0.292048</td>\n",
       "      <td>-0.355501</td>\n",
       "      <td>0.128069</td>\n",
       "      <td>-0.613808</td>\n",
       "      <td>0.695360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>0.203784</td>\n",
       "      <td>0.352734</td>\n",
       "      <td>-0.569537</td>\n",
       "      <td>0.644779</td>\n",
       "      <td>0.086518</td>\n",
       "      <td>0.731470</td>\n",
       "      <td>-0.240265</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.747881</td>\n",
       "      <td>0.456022</td>\n",
       "      <td>0.506456</td>\n",
       "      <td>0.261515</td>\n",
       "      <td>-0.273534</td>\n",
       "      <td>0.602339</td>\n",
       "      <td>-0.376955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dis</th>\n",
       "      <td>-0.302211</td>\n",
       "      <td>-0.379670</td>\n",
       "      <td>0.664408</td>\n",
       "      <td>-0.708027</td>\n",
       "      <td>-0.099176</td>\n",
       "      <td>-0.769230</td>\n",
       "      <td>0.205246</td>\n",
       "      <td>-0.747881</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.494588</td>\n",
       "      <td>-0.534432</td>\n",
       "      <td>-0.232471</td>\n",
       "      <td>0.291512</td>\n",
       "      <td>-0.496996</td>\n",
       "      <td>0.249929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rad</th>\n",
       "      <td>0.686002</td>\n",
       "      <td>0.625505</td>\n",
       "      <td>-0.311948</td>\n",
       "      <td>0.595129</td>\n",
       "      <td>-0.007368</td>\n",
       "      <td>0.611441</td>\n",
       "      <td>-0.209847</td>\n",
       "      <td>0.456022</td>\n",
       "      <td>-0.494588</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.910228</td>\n",
       "      <td>0.464741</td>\n",
       "      <td>-0.444413</td>\n",
       "      <td>0.488676</td>\n",
       "      <td>-0.381626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tax</th>\n",
       "      <td>0.666626</td>\n",
       "      <td>0.582764</td>\n",
       "      <td>-0.314563</td>\n",
       "      <td>0.720760</td>\n",
       "      <td>-0.035587</td>\n",
       "      <td>0.668023</td>\n",
       "      <td>-0.292048</td>\n",
       "      <td>0.506456</td>\n",
       "      <td>-0.534432</td>\n",
       "      <td>0.910228</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.460853</td>\n",
       "      <td>-0.441808</td>\n",
       "      <td>0.543993</td>\n",
       "      <td>-0.468536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ptratio</th>\n",
       "      <td>0.291074</td>\n",
       "      <td>0.289946</td>\n",
       "      <td>-0.391679</td>\n",
       "      <td>0.383248</td>\n",
       "      <td>-0.121515</td>\n",
       "      <td>0.188933</td>\n",
       "      <td>-0.355501</td>\n",
       "      <td>0.261515</td>\n",
       "      <td>-0.232471</td>\n",
       "      <td>0.464741</td>\n",
       "      <td>0.460853</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.177383</td>\n",
       "      <td>0.374044</td>\n",
       "      <td>-0.507787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>black</th>\n",
       "      <td>-0.295041</td>\n",
       "      <td>-0.385064</td>\n",
       "      <td>0.175520</td>\n",
       "      <td>-0.356977</td>\n",
       "      <td>0.048788</td>\n",
       "      <td>-0.380051</td>\n",
       "      <td>0.128069</td>\n",
       "      <td>-0.273534</td>\n",
       "      <td>0.291512</td>\n",
       "      <td>-0.444413</td>\n",
       "      <td>-0.441808</td>\n",
       "      <td>-0.177383</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.366087</td>\n",
       "      <td>0.333461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lstat</th>\n",
       "      <td>0.258465</td>\n",
       "      <td>0.455621</td>\n",
       "      <td>-0.412995</td>\n",
       "      <td>0.603800</td>\n",
       "      <td>-0.053929</td>\n",
       "      <td>0.590879</td>\n",
       "      <td>-0.613808</td>\n",
       "      <td>0.602339</td>\n",
       "      <td>-0.496996</td>\n",
       "      <td>0.488676</td>\n",
       "      <td>0.543993</td>\n",
       "      <td>0.374044</td>\n",
       "      <td>-0.366087</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.737663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>medv</th>\n",
       "      <td>-0.226604</td>\n",
       "      <td>-0.388305</td>\n",
       "      <td>0.360445</td>\n",
       "      <td>-0.483725</td>\n",
       "      <td>0.175260</td>\n",
       "      <td>-0.427321</td>\n",
       "      <td>0.695360</td>\n",
       "      <td>-0.376955</td>\n",
       "      <td>0.249929</td>\n",
       "      <td>-0.381626</td>\n",
       "      <td>-0.468536</td>\n",
       "      <td>-0.507787</td>\n",
       "      <td>0.333461</td>\n",
       "      <td>-0.737663</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Unnamed: 0      crim        zn     indus      chas       nox  \\\n",
       "Unnamed: 0    1.000000  0.407407 -0.103393  0.399439 -0.003759  0.398736   \n",
       "crim          0.407407  1.000000 -0.200469  0.406583 -0.055892  0.420972   \n",
       "zn           -0.103393 -0.200469  1.000000 -0.533828 -0.042697 -0.516604   \n",
       "indus         0.399439  0.406583 -0.533828  1.000000  0.062938  0.763651   \n",
       "chas         -0.003759 -0.055892 -0.042697  0.062938  1.000000  0.091203   \n",
       "nox           0.398736  0.420972 -0.516604  0.763651  0.091203  1.000000   \n",
       "rm           -0.079971 -0.219247  0.311991 -0.391676  0.091251 -0.302188   \n",
       "age           0.203784  0.352734 -0.569537  0.644779  0.086518  0.731470   \n",
       "dis          -0.302211 -0.379670  0.664408 -0.708027 -0.099176 -0.769230   \n",
       "rad           0.686002  0.625505 -0.311948  0.595129 -0.007368  0.611441   \n",
       "tax           0.666626  0.582764 -0.314563  0.720760 -0.035587  0.668023   \n",
       "ptratio       0.291074  0.289946 -0.391679  0.383248 -0.121515  0.188933   \n",
       "black        -0.295041 -0.385064  0.175520 -0.356977  0.048788 -0.380051   \n",
       "lstat         0.258465  0.455621 -0.412995  0.603800 -0.053929  0.590879   \n",
       "medv         -0.226604 -0.388305  0.360445 -0.483725  0.175260 -0.427321   \n",
       "\n",
       "                  rm       age       dis       rad       tax   ptratio  \\\n",
       "Unnamed: 0 -0.079971  0.203784 -0.302211  0.686002  0.666626  0.291074   \n",
       "crim       -0.219247  0.352734 -0.379670  0.625505  0.582764  0.289946   \n",
       "zn          0.311991 -0.569537  0.664408 -0.311948 -0.314563 -0.391679   \n",
       "indus      -0.391676  0.644779 -0.708027  0.595129  0.720760  0.383248   \n",
       "chas        0.091251  0.086518 -0.099176 -0.007368 -0.035587 -0.121515   \n",
       "nox        -0.302188  0.731470 -0.769230  0.611441  0.668023  0.188933   \n",
       "rm          1.000000 -0.240265  0.205246 -0.209847 -0.292048 -0.355501   \n",
       "age        -0.240265  1.000000 -0.747881  0.456022  0.506456  0.261515   \n",
       "dis         0.205246 -0.747881  1.000000 -0.494588 -0.534432 -0.232471   \n",
       "rad        -0.209847  0.456022 -0.494588  1.000000  0.910228  0.464741   \n",
       "tax        -0.292048  0.506456 -0.534432  0.910228  1.000000  0.460853   \n",
       "ptratio    -0.355501  0.261515 -0.232471  0.464741  0.460853  1.000000   \n",
       "black       0.128069 -0.273534  0.291512 -0.444413 -0.441808 -0.177383   \n",
       "lstat      -0.613808  0.602339 -0.496996  0.488676  0.543993  0.374044   \n",
       "medv        0.695360 -0.376955  0.249929 -0.381626 -0.468536 -0.507787   \n",
       "\n",
       "               black     lstat      medv  \n",
       "Unnamed: 0 -0.295041  0.258465 -0.226604  \n",
       "crim       -0.385064  0.455621 -0.388305  \n",
       "zn          0.175520 -0.412995  0.360445  \n",
       "indus      -0.356977  0.603800 -0.483725  \n",
       "chas        0.048788 -0.053929  0.175260  \n",
       "nox        -0.380051  0.590879 -0.427321  \n",
       "rm          0.128069 -0.613808  0.695360  \n",
       "age        -0.273534  0.602339 -0.376955  \n",
       "dis         0.291512 -0.496996  0.249929  \n",
       "rad        -0.444413  0.488676 -0.381626  \n",
       "tax        -0.441808  0.543993 -0.468536  \n",
       "ptratio    -0.177383  0.374044 -0.507787  \n",
       "black       1.000000 -0.366087  0.333461  \n",
       "lstat      -0.366087  1.000000 -0.737663  \n",
       "medv        0.333461 -0.737663  1.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"The most important trick was to see the data correlation \n",
    "the relation between the dependent and independent columns\n",
    "The correction will see with the \n",
    "-1 highly negatively correlated means they are oppposing more \n",
    "0 there is no correlation in between dependent and the independent terms\n",
    "1 highly positively correlation there more correlation in between the dependent and the independent\"\"\"\n",
    "\n",
    "data.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>Unnamed: 0</th>\n",
       "      <th>crim</th>\n",
       "      <th>zn</th>\n",
       "      <th>indus</th>\n",
       "      <th>chas</th>\n",
       "      <th>nox</th>\n",
       "      <th>rm</th>\n",
       "      <th>age</th>\n",
       "      <th>dis</th>\n",
       "      <th>rad</th>\n",
       "      <th>tax</th>\n",
       "      <th>ptratio</th>\n",
       "      <th>black</th>\n",
       "      <th>lstat</th>\n",
       "      <th>medv</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>253.500000</td>\n",
       "      <td>3.613524</td>\n",
       "      <td>11.363636</td>\n",
       "      <td>11.136779</td>\n",
       "      <td>0.069170</td>\n",
       "      <td>0.554695</td>\n",
       "      <td>6.284634</td>\n",
       "      <td>68.574901</td>\n",
       "      <td>3.795043</td>\n",
       "      <td>9.549407</td>\n",
       "      <td>408.237154</td>\n",
       "      <td>18.455534</td>\n",
       "      <td>356.674032</td>\n",
       "      <td>12.653063</td>\n",
       "      <td>22.532806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>146.213884</td>\n",
       "      <td>8.601545</td>\n",
       "      <td>23.322453</td>\n",
       "      <td>6.860353</td>\n",
       "      <td>0.253994</td>\n",
       "      <td>0.115878</td>\n",
       "      <td>0.702617</td>\n",
       "      <td>28.148861</td>\n",
       "      <td>2.105710</td>\n",
       "      <td>8.707259</td>\n",
       "      <td>168.537116</td>\n",
       "      <td>2.164946</td>\n",
       "      <td>91.294864</td>\n",
       "      <td>7.141062</td>\n",
       "      <td>9.197104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.006320</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.460000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.385000</td>\n",
       "      <td>3.561000</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>1.129600</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>12.600000</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>1.730000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>127.250000</td>\n",
       "      <td>0.082045</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.190000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.449000</td>\n",
       "      <td>5.885500</td>\n",
       "      <td>45.025000</td>\n",
       "      <td>2.100175</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>279.000000</td>\n",
       "      <td>17.400000</td>\n",
       "      <td>375.377500</td>\n",
       "      <td>6.950000</td>\n",
       "      <td>17.025000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>253.500000</td>\n",
       "      <td>0.256510</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.690000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.538000</td>\n",
       "      <td>6.208500</td>\n",
       "      <td>77.500000</td>\n",
       "      <td>3.207450</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>330.000000</td>\n",
       "      <td>19.050000</td>\n",
       "      <td>391.440000</td>\n",
       "      <td>11.360000</td>\n",
       "      <td>21.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>379.750000</td>\n",
       "      <td>3.677082</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>18.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.624000</td>\n",
       "      <td>6.623500</td>\n",
       "      <td>94.075000</td>\n",
       "      <td>5.188425</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>666.000000</td>\n",
       "      <td>20.200000</td>\n",
       "      <td>396.225000</td>\n",
       "      <td>16.955000</td>\n",
       "      <td>25.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>506.000000</td>\n",
       "      <td>88.976200</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>27.740000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.871000</td>\n",
       "      <td>8.780000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>12.126500</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>711.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>396.900000</td>\n",
       "      <td>37.970000</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0        crim          zn       indus        chas         nox  \\\n",
       "count  506.000000  506.000000  506.000000  506.000000  506.000000  506.000000   \n",
       "mean   253.500000    3.613524   11.363636   11.136779    0.069170    0.554695   \n",
       "std    146.213884    8.601545   23.322453    6.860353    0.253994    0.115878   \n",
       "min      1.000000    0.006320    0.000000    0.460000    0.000000    0.385000   \n",
       "25%    127.250000    0.082045    0.000000    5.190000    0.000000    0.449000   \n",
       "50%    253.500000    0.256510    0.000000    9.690000    0.000000    0.538000   \n",
       "75%    379.750000    3.677082   12.500000   18.100000    0.000000    0.624000   \n",
       "max    506.000000   88.976200  100.000000   27.740000    1.000000    0.871000   \n",
       "\n",
       "               rm         age         dis         rad         tax     ptratio  \\\n",
       "count  506.000000  506.000000  506.000000  506.000000  506.000000  506.000000   \n",
       "mean     6.284634   68.574901    3.795043    9.549407  408.237154   18.455534   \n",
       "std      0.702617   28.148861    2.105710    8.707259  168.537116    2.164946   \n",
       "min      3.561000    2.900000    1.129600    1.000000  187.000000   12.600000   \n",
       "25%      5.885500   45.025000    2.100175    4.000000  279.000000   17.400000   \n",
       "50%      6.208500   77.500000    3.207450    5.000000  330.000000   19.050000   \n",
       "75%      6.623500   94.075000    5.188425   24.000000  666.000000   20.200000   \n",
       "max      8.780000  100.000000   12.126500   24.000000  711.000000   22.000000   \n",
       "\n",
       "            black       lstat        medv  \n",
       "count  506.000000  506.000000  506.000000  \n",
       "mean   356.674032   12.653063   22.532806  \n",
       "std     91.294864    7.141062    9.197104  \n",
       "min      0.320000    1.730000    5.000000  \n",
       "25%    375.377500    6.950000   17.025000  \n",
       "50%    391.440000   11.360000   21.200000  \n",
       "75%    396.225000   16.955000   25.000000  \n",
       "max    396.900000   37.970000   50.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"describing the data see which column has more std, mean, median, etc\"\"\"\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"The most important was droppping the columns from the data\n",
    "we think some columns are not used in the data \n",
    "we drop columns by see correlation tabel of the data\n",
    "in the correlation tabel most of the coulns are negatively correlates\n",
    "i will drop some columns by seeing data randomly\n",
    "There is no use of the \n",
    "Unnamed: 0\t\n",
    "zn, chas\"\"\"\n",
    "\n",
    "data = data.drop(columns = ['Unnamed: 0','zn','chas','black','tax'], axis = 0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crim</th>\n",
       "      <th>indus</th>\n",
       "      <th>nox</th>\n",
       "      <th>rm</th>\n",
       "      <th>age</th>\n",
       "      <th>dis</th>\n",
       "      <th>rad</th>\n",
       "      <th>ptratio</th>\n",
       "      <th>lstat</th>\n",
       "      <th>medv</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00632</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.0900</td>\n",
       "      <td>1</td>\n",
       "      <td>15.3</td>\n",
       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02731</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2</td>\n",
       "      <td>17.8</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02729</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2</td>\n",
       "      <td>17.8</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03237</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>18.7</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>18.7</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      crim  indus    nox     rm   age     dis  rad  ptratio  lstat  medv\n",
       "0  0.00632   2.31  0.538  6.575  65.2  4.0900    1     15.3   4.98  24.0\n",
       "1  0.02731   7.07  0.469  6.421  78.9  4.9671    2     17.8   9.14  21.6\n",
       "2  0.02729   7.07  0.469  7.185  61.1  4.9671    2     17.8   4.03  34.7\n",
       "3  0.03237   2.18  0.458  6.998  45.8  6.0622    3     18.7   2.94  33.4\n",
       "4  0.06905   2.18  0.458  7.147  54.2  6.0622    3     18.7   5.33  36.2"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\"\"\"NOW we have clean data i think \n",
    "NO NULL VALUES \n",
    "NO UNWANTED DATA COLUMNS\"\"\"\n",
    "\n",
    "#FEATURES of the data\n",
    "X = data.iloc[:, :-1].values\n",
    "#ILOC WILL SEE THE LOCATION OF THE COLUMNS AND VALUES WILL BRING DATA FROM DATAFRAME TO NUMPY ARRAY\n",
    "y = data.iloc[:, -1].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(X) #this was changed from pandas to numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state = 0, test_size = 0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/sai/anaconda3/lib/python3.6/site-packages/sklearn/svm/base.py:196: FutureWarning: The default value of gamma will change from 'auto' to 'scale' in version 0.22 to account better for unscaled features. Set gamma explicitly to 'auto' or 'scale' to avoid this warning.\n",
      "  \"avoid this warning.\", FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "SVR(C=2, cache_size=200, coef0=0.0, degree=2, epsilon=0.1,\n",
       "  gamma='auto_deprecated', kernel='rbf', max_iter=-1, shrinking=True,\n",
       "  tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.svm import SVR\n",
    "svm = SVR(C = 2, kernel = 'rbf', degree = 2)\n",
    "svm.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_pred = svm.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "69.746629218709288"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "mean_squared_error(y_test, y_pred)"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
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