1.SVMR.ipynb

{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"id":"txmCBhMIacF6"},"outputs":[],"source":["import pandas as pd"]},{"cell_type":"code","source":["from google.colab import drive\n","\n","# Mount your Google Drive\n","drive.mount('/content/drive')\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"bH3s1CXlahrX","executionInfo":{"status":"ok","timestamp":1690361833627,"user_tz":-330,"elapsed":23429,"user":{"displayName":"Mohamed Fazil","userId":"10693351885823441949"}},"outputId":"6dca79b3-3d77-4695-b004-29d2cbf4952c"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","execution_count":null,"metadata":{"id":"imovAyfsacF7"},"outputs":[],"source":["dataset=pd.read_csv(\"/content/drive/MyDrive/Colab Notebooks/Machine Learning-Regression/1.Traditional Way/3.Support Vector Machine/50_Startups.csv\")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"Cp6y0K4kacF7","executionInfo":{"status":"ok","timestamp":1690361880722,"user_tz":-330,"elapsed":9,"user":{"displayName":"Mohamed Fazil","userId":"10693351885823441949"}},"outputId":"f9a74510-5482-4c34-d0a7-b51015fc171b"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["    R&D Spend  Administration  Marketing Spend       State     Profit\n","0   165349.20       136897.80        471784.10    New York  192261.83\n","1   162597.70       151377.59        443898.53  California  191792.06\n","2   153441.51       101145.55        407934.54     Florida  191050.39\n","3   144372.41       118671.85        383199.62    New York  182901.99\n","4   142107.34        91391.77        366168.42     Florida  166187.94\n","5   131876.90        99814.71        362861.36    New York  156991.12\n","6   134615.46       147198.87        127716.82  California  156122.51\n","7   130298.13       145530.06        323876.68     Florida  155752.60\n","8   120542.52       148718.95        311613.29    New York  152211.77\n","9   123334.88       108679.17        304981.62  California  149759.96\n","10  101913.08       110594.11        229160.95     Florida  146121.95\n","11  100671.96        91790.61        249744.55  California  144259.40\n","12   93863.75       127320.38        249839.44     Florida  141585.52\n","13   91992.39       135495.07        252664.93  California  134307.35\n","14  119943.24       156547.42        256512.92     Florida  132602.65\n","15  114523.61       122616.84        261776.23    New York  129917.04\n","16   78013.11       121597.55        264346.06  California  126992.93\n","17   94657.16       145077.58        282574.31    New York  125370.37\n","18   91749.16       114175.79        294919.57     Florida  124266.90\n","19   86419.70       153514.11             0.00    New York  122776.86\n","20   76253.86       113867.30        298664.47  California  118474.03\n","21   78389.47       153773.43        299737.29    New York  111313.02\n","22   73994.56       122782.75        303319.26     Florida  110352.25\n","23   67532.53       105751.03        304768.73     Florida  108733.99\n","24   77044.01        99281.34        140574.81    New York  108552.04\n","25   64664.71       139553.16        137962.62  California  107404.34\n","26   75328.87       144135.98        134050.07     Florida  105733.54\n","27   72107.60       127864.55        353183.81    New York  105008.31\n","28   66051.52       182645.56        118148.20     Florida  103282.38\n","29   65605.48       153032.06        107138.38    New York  101004.64\n","30   61994.48       115641.28         91131.24     Florida   99937.59\n","31   61136.38       152701.92         88218.23    New York   97483.56\n","32   63408.86       129219.61         46085.25  California   97427.84\n","33   55493.95       103057.49        214634.81     Florida   96778.92\n","34   46426.07       157693.92        210797.67  California   96712.80\n","35   46014.02        85047.44        205517.64    New York   96479.51\n","36   28663.76       127056.21        201126.82     Florida   90708.19\n","37   44069.95        51283.14        197029.42  California   89949.14\n","38   20229.59        65947.93        185265.10    New York   81229.06\n","39   38558.51        82982.09        174999.30  California   81005.76\n","40   28754.33       118546.05        172795.67  California   78239.91\n","41   27892.92        84710.77        164470.71     Florida   77798.83\n","42   23640.93        96189.63        148001.11  California   71498.49\n","43   15505.73       127382.30         35534.17    New York   69758.98\n","44   22177.74       154806.14         28334.72  California   65200.33\n","45    1000.23       124153.04          1903.93    New York   64926.08\n","46    1315.46       115816.21        297114.46     Florida   49490.75\n","47       0.00       135426.92             0.00  California   42559.73\n","48     542.05        51743.15             0.00    New York   35673.41\n","49       0.00       116983.80         45173.06  California   14681.40"],"text/html":["\n","\n","  <div id=\"df-fb8748cb-bd4a-4d66-9d8b-83b119441613\">\n","    <div class=\"colab-df-container\">\n","      <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>R&amp;D Spend</th>\n","      <th>Administration</th>\n","      <th>Marketing Spend</th>\n","      <th>State</th>\n","      <th>Profit</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>165349.20</td>\n","      <td>136897.80</td>\n","      <td>471784.10</td>\n","      <td>New York</td>\n","      <td>192261.83</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>162597.70</td>\n","      <td>151377.59</td>\n","      <td>443898.53</td>\n","      <td>California</td>\n","      <td>191792.06</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>153441.51</td>\n","      <td>101145.55</td>\n","      <td>407934.54</td>\n","      <td>Florida</td>\n","      <td>191050.39</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>144372.41</td>\n","      <td>118671.85</td>\n","      <td>383199.62</td>\n","      <td>New York</td>\n","      <td>182901.99</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>142107.34</td>\n","      <td>91391.77</td>\n","      <td>366168.42</td>\n","      <td>Florida</td>\n","      <td>166187.94</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>131876.90</td>\n","      <td>99814.71</td>\n","      <td>362861.36</td>\n","      <td>New York</td>\n","      <td>156991.12</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>134615.46</td>\n","      <td>147198.87</td>\n","      <td>127716.82</td>\n","      <td>California</td>\n","      <td>156122.51</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>130298.13</td>\n","      <td>145530.06</td>\n","      <td>323876.68</td>\n","      <td>Florida</td>\n","      <td>155752.60</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>120542.52</td>\n","      <td>148718.95</td>\n","      <td>311613.29</td>\n","      <td>New York</td>\n","      <td>152211.77</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>123334.88</td>\n","      <td>108679.17</td>\n","      <td>304981.62</td>\n","      <td>California</td>\n","      <td>149759.96</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>101913.08</td>\n","      <td>110594.11</td>\n","      <td>229160.95</td>\n","      <td>Florida</td>\n","      <td>146121.95</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>100671.96</td>\n","      <td>91790.61</td>\n","      <td>249744.55</td>\n","      <td>California</td>\n","      <td>144259.40</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>93863.75</td>\n","      <td>127320.38</td>\n","      <td>249839.44</td>\n","      <td>Florida</td>\n","      <td>141585.52</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>91992.39</td>\n","      <td>135495.07</td>\n","      <td>252664.93</td>\n","      <td>California</td>\n","      <td>134307.35</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>119943.24</td>\n","      <td>156547.42</td>\n","      <td>256512.92</td>\n","      <td>Florida</td>\n","      <td>132602.65</td>\n","    </tr>\n","    <tr>\n","      <th>15</th>\n","      <td>114523.61</td>\n","      <td>122616.84</td>\n","      <td>261776.23</td>\n","      <td>New York</td>\n","      <td>129917.04</td>\n","    </tr>\n","    <tr>\n","      <th>16</th>\n","      <td>78013.11</td>\n","      <td>121597.55</td>\n","      <td>264346.06</td>\n","      <td>California</td>\n","      <td>126992.93</td>\n","    </tr>\n","    <tr>\n","      <th>17</th>\n","      <td>94657.16</td>\n","      <td>145077.58</td>\n","      <td>282574.31</td>\n","      <td>New York</td>\n","      <td>125370.37</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>91749.16</td>\n","      <td>114175.79</td>\n","      <td>294919.57</td>\n","      <td>Florida</td>\n","      <td>124266.90</td>\n","    </tr>\n","    <tr>\n","      <th>19</th>\n","      <td>86419.70</td>\n","      <td>153514.11</td>\n","      <td>0.00</td>\n","      <td>New York</td>\n","      <td>122776.86</td>\n","    </tr>\n","    <tr>\n","      <th>20</th>\n","      <td>76253.86</td>\n","      <td>113867.30</td>\n","      <td>298664.47</td>\n","      <td>California</td>\n","      <td>118474.03</td>\n","    </tr>\n","    <tr>\n","      <th>21</th>\n","      <td>78389.47</td>\n","      <td>153773.43</td>\n","      <td>299737.29</td>\n","      <td>New York</td>\n","      <td>111313.02</td>\n","    </tr>\n","    <tr>\n","      <th>22</th>\n","      <td>73994.56</td>\n","      <td>122782.75</td>\n","      <td>303319.26</td>\n","      <td>Florida</td>\n","      <td>110352.25</td>\n","    </tr>\n","    <tr>\n","      <th>23</th>\n","      <td>67532.53</td>\n","      <td>105751.03</td>\n","      <td>304768.73</td>\n","      <td>Florida</td>\n","      <td>108733.99</td>\n","    </tr>\n","    <tr>\n","      <th>24</th>\n","      <td>77044.01</td>\n","      <td>99281.34</td>\n","      <td>140574.81</td>\n","      <td>New York</td>\n","      <td>108552.04</td>\n","    </tr>\n","    <tr>\n","      <th>25</th>\n","      <td>64664.71</td>\n","      <td>139553.16</td>\n","      <td>137962.62</td>\n","      <td>California</td>\n","      <td>107404.34</td>\n","    </tr>\n","    <tr>\n","      <th>26</th>\n","      <td>75328.87</td>\n","      <td>144135.98</td>\n","      <td>134050.07</td>\n","      <td>Florida</td>\n","      <td>105733.54</td>\n","    </tr>\n","    <tr>\n","      <th>27</th>\n","      <td>72107.60</td>\n","      <td>127864.55</td>\n","      <td>353183.81</td>\n","      <td>New York</td>\n","      <td>105008.31</td>\n","    </tr>\n","    <tr>\n","      <th>28</th>\n","      <td>66051.52</td>\n","      <td>182645.56</td>\n","      <td>118148.20</td>\n","      <td>Florida</td>\n","      <td>103282.38</td>\n","    </tr>\n","    <tr>\n","      <th>29</th>\n","      <td>65605.48</td>\n","      <td>153032.06</td>\n","      <td>107138.38</td>\n","      <td>New York</td>\n","      <td>101004.64</td>\n","    </tr>\n","    <tr>\n","      <th>30</th>\n","      <td>61994.48</td>\n","      <td>115641.28</td>\n","      <td>91131.24</td>\n","      <td>Florida</td>\n","      <td>99937.59</td>\n","    </tr>\n","    <tr>\n","      <th>31</th>\n","      <td>61136.38</td>\n","      <td>152701.92</td>\n","      <td>88218.23</td>\n","      <td>New York</td>\n","      <td>97483.56</td>\n","    </tr>\n","    <tr>\n","      <th>32</th>\n","      <td>63408.86</td>\n","      <td>129219.61</td>\n","      <td>46085.25</td>\n","      <td>California</td>\n","      <td>97427.84</td>\n","    </tr>\n","    <tr>\n","      <th>33</th>\n","      <td>55493.95</td>\n","      <td>103057.49</td>\n","      <td>214634.81</td>\n","      <td>Florida</td>\n","      <td>96778.92</td>\n","    </tr>\n","    <tr>\n","      <th>34</th>\n","      <td>46426.07</td>\n","      <td>157693.92</td>\n","      <td>210797.67</td>\n","      <td>California</td>\n","      <td>96712.80</td>\n","    </tr>\n","    <tr>\n","      <th>35</th>\n","      <td>46014.02</td>\n","      <td>85047.44</td>\n","      <td>205517.64</td>\n","      <td>New York</td>\n","      <td>96479.51</td>\n","    </tr>\n","    <tr>\n","      <th>36</th>\n","      <td>28663.76</td>\n","      <td>127056.21</td>\n","      <td>201126.82</td>\n","      <td>Florida</td>\n","      <td>90708.19</td>\n","    </tr>\n","    <tr>\n","      <th>37</th>\n","      <td>44069.95</td>\n","      <td>51283.14</td>\n","      <td>197029.42</td>\n","      <td>California</td>\n","      <td>89949.14</td>\n","    </tr>\n","    <tr>\n","      <th>38</th>\n","      <td>20229.59</td>\n","      <td>65947.93</td>\n","      <td>185265.10</td>\n","      <td>New York</td>\n","      <td>81229.06</td>\n","    </tr>\n","    <tr>\n","      <th>39</th>\n","      <td>38558.51</td>\n","      <td>82982.09</td>\n","      <td>174999.30</td>\n","      <td>California</td>\n","      <td>81005.76</td>\n","    </tr>\n","    <tr>\n","      <th>40</th>\n","      <td>28754.33</td>\n","      <td>118546.05</td>\n","      <td>172795.67</td>\n","      <td>California</td>\n","      <td>78239.91</td>\n","    </tr>\n","    <tr>\n","      <th>41</th>\n","      <td>27892.92</td>\n","      <td>84710.77</td>\n","      <td>164470.71</td>\n","      <td>Florida</td>\n","      <td>77798.83</td>\n","    </tr>\n","    <tr>\n","      <th>42</th>\n","      <td>23640.93</td>\n","      <td>96189.63</td>\n","      <td>148001.11</td>\n","      <td>California</td>\n","      <td>71498.49</td>\n","    </tr>\n","    <tr>\n","      <th>43</th>\n","      <td>15505.73</td>\n","      <td>127382.30</td>\n","      <td>35534.17</td>\n","      <td>New York</td>\n","      <td>69758.98</td>\n","    </tr>\n","    <tr>\n","      <th>44</th>\n","      <td>22177.74</td>\n","      <td>154806.14</td>\n","      <td>28334.72</td>\n","      <td>California</td>\n","      <td>65200.33</td>\n","    </tr>\n","    <tr>\n","      <th>45</th>\n","      <td>1000.23</td>\n","      <td>124153.04</td>\n","      <td>1903.93</td>\n","      <td>New York</td>\n","      <td>64926.08</td>\n","    </tr>\n","    <tr>\n","      <th>46</th>\n","      <td>1315.46</td>\n","      <td>115816.21</td>\n","      <td>297114.46</td>\n","      <td>Florida</td>\n","      <td>49490.75</td>\n","    </tr>\n","    <tr>\n","      <th>47</th>\n","      <td>0.00</td>\n","      <td>135426.92</td>\n","      <td>0.00</td>\n","      <td>California</td>\n","      <td>42559.73</td>\n","    </tr>\n","    <tr>\n","      <th>48</th>\n","      <td>542.05</td>\n","      <td>51743.15</td>\n","      <td>0.00</td>\n","      <td>New York</td>\n","      <td>35673.41</td>\n","    </tr>\n","    <tr>\n","      <th>49</th>\n","      <td>0.00</td>\n","      <td>116983.80</td>\n","      <td>45173.06</td>\n","      <td>California</td>\n","      <td>14681.40</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fb8748cb-bd4a-4d66-9d8b-83b119441613')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" 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182901.99              0   \n","4   142107.34        91391.77        366168.42  166187.94              1   \n","5   131876.90        99814.71        362861.36  156991.12              0   \n","6   134615.46       147198.87        127716.82  156122.51              0   \n","7   130298.13       145530.06        323876.68  155752.60              1   \n","8   120542.52       148718.95        311613.29  152211.77              0   \n","9   123334.88       108679.17        304981.62  149759.96              0   \n","10  101913.08       110594.11        229160.95  146121.95              1   \n","11  100671.96        91790.61        249744.55  144259.40              0   \n","12   93863.75       127320.38        249839.44  141585.52              1   \n","13   91992.39       135495.07        252664.93  134307.35              0   \n","14  119943.24       156547.42        256512.92  132602.65              1   \n","15  114523.61       122616.84        261776.23  129917.04              0   \n","16   78013.11       121597.55        264346.06  126992.93              0   \n","17   94657.16       145077.58        282574.31  125370.37              0   \n","18   91749.16       114175.79        294919.57  124266.90              1   \n","19   86419.70       153514.11             0.00  122776.86              0   \n","20   76253.86       113867.30        298664.47  118474.03              0   \n","21   78389.47       153773.43        299737.29  111313.02              0   \n","22   73994.56       122782.75        303319.26  110352.25              1   \n","23   67532.53       105751.03        304768.73  108733.99              1   \n","24   77044.01        99281.34        140574.81  108552.04              0   \n","25   64664.71       139553.16        137962.62  107404.34              0   \n","26   75328.87       144135.98        134050.07  105733.54              1   \n","27   72107.60       127864.55        353183.81  105008.31              0   \n","28   66051.52       182645.56        118148.20  103282.38              1   \n","29   65605.48       153032.06        107138.38  101004.64              0   \n","30   61994.48       115641.28         91131.24   99937.59              1   \n","31   61136.38       152701.92         88218.23   97483.56              0   \n","32   63408.86       129219.61         46085.25   97427.84              0   \n","33   55493.95       103057.49        214634.81   96778.92              1   \n","34   46426.07       157693.92        210797.67   96712.80              0   \n","35   46014.02        85047.44        205517.64   96479.51              0   \n","36   28663.76       127056.21        201126.82   90708.19              1   \n","37   44069.95        51283.14        197029.42   89949.14              0   \n","38   20229.59        65947.93        185265.10   81229.06              0   \n","39   38558.51        82982.09        174999.30   81005.76              0   \n","40   28754.33       118546.05        172795.67   78239.91              0   \n","41   27892.92        84710.77        164470.71   77798.83              1   \n","42   23640.93        96189.63        148001.11   71498.49              0   \n","43   15505.73       127382.30         35534.17   69758.98              0   \n","44   22177.74       154806.14         28334.72   65200.33              0   \n","45    1000.23       124153.04          1903.93   64926.08              0   \n","46    1315.46       115816.21        297114.46   49490.75              1   \n","47       0.00       135426.92             0.00   42559.73              0   \n","48     542.05        51743.15             0.00   35673.41              0   \n","49       0.00       116983.80         45173.06   14681.40              0   \n","\n","    State_New York  \n","0                1  \n","1                0  \n","2                0  \n","3                1  \n","4                0  \n","5                1  \n","6                0  \n","7                0  \n","8                1  \n","9                0  \n","10               0  \n","11               0  \n","12               0  \n","13               0  \n","14               0  \n","15               1  \n","16               0  \n","17               1  \n","18               0  \n","19               1  \n","20               0  \n","21               1  \n","22               0  \n","23               0  \n","24               1  \n","25               0  \n","26               0  \n","27               1  \n","28               0  \n","29               1  \n","30               0  \n","31               1  \n","32               0  \n","33               0  \n","34               0  \n","35               1  \n","36               0  \n","37               0  \n","38               1  \n","39               0  \n","40               0  \n","41               0  \n","42               0  \n","43               1  \n","44               0  \n","45               1  \n","46               0  \n","47               0  \n","48               1  \n","49               0  "],"text/html":["\n","\n","  <div id=\"df-34dad13a-07d4-4fa9-bff1-69d8061f6703\">\n","    <div class=\"colab-df-container\">\n","      <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>R&amp;D Spend</th>\n","      <th>Administration</th>\n","      <th>Marketing Spend</th>\n","      <th>Profit</th>\n","      <th>State_Florida</th>\n","      <th>State_New York</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>165349.20</td>\n","      <td>136897.80</td>\n","      <td>471784.10</td>\n","      <td>192261.83</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>162597.70</td>\n","      <td>151377.59</td>\n","      <td>443898.53</td>\n","      <td>191792.06</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>153441.51</td>\n","      <td>101145.55</td>\n","      <td>407934.54</td>\n","      <td>191050.39</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>144372.41</td>\n","      <td>118671.85</td>\n","      <td>383199.62</td>\n","      <td>182901.99</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>142107.34</td>\n","      <td>91391.77</td>\n","      <td>366168.42</td>\n","      <td>166187.94</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>131876.90</td>\n","      <td>99814.71</td>\n","      <td>362861.36</td>\n","      <td>156991.12</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>134615.46</td>\n","      <td>147198.87</td>\n","      <td>127716.82</td>\n","      <td>156122.51</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>130298.13</td>\n","      <td>145530.06</td>\n","      <td>323876.68</td>\n","      <td>155752.60</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>120542.52</td>\n","      <td>148718.95</td>\n","      <td>311613.29</td>\n","      <td>152211.77</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>123334.88</td>\n","      <td>108679.17</td>\n","      <td>304981.62</td>\n","      <td>149759.96</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>101913.08</td>\n","      <td>110594.11</td>\n","      <td>229160.95</td>\n","      <td>146121.95</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>100671.96</td>\n","      <td>91790.61</td>\n","      <td>249744.55</td>\n","      <td>144259.40</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>93863.75</td>\n","      <td>127320.38</td>\n","      <td>249839.44</td>\n","      <td>141585.52</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>91992.39</td>\n","      <td>135495.07</td>\n","      <td>252664.93</td>\n","      <td>134307.35</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>119943.24</td>\n","      <td>156547.42</td>\n","      <td>256512.92</td>\n","      <td>132602.65</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>15</th>\n","      <td>114523.61</td>\n","      <td>122616.84</td>\n","      <td>261776.23</td>\n","      <td>129917.04</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>16</th>\n","      <td>78013.11</td>\n","      <td>121597.55</td>\n","      <td>264346.06</td>\n","      <td>126992.93</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>17</th>\n","      <td>94657.16</td>\n","      <td>145077.58</td>\n","      <td>282574.31</td>\n","      <td>125370.37</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>91749.16</td>\n","      <td>114175.79</td>\n","      <td>294919.57</td>\n","      <td>124266.90</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>19</th>\n","      <td>86419.70</td>\n","      <td>153514.11</td>\n","      <td>0.00</td>\n","      <td>122776.86</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>20</th>\n","      <td>76253.86</td>\n","      <td>113867.30</td>\n","      <td>298664.47</td>\n","      <td>118474.03</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>21</th>\n","      <td>78389.47</td>\n","      <td>153773.43</td>\n","      <td>299737.29</td>\n","      <td>111313.02</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>22</th>\n","      <td>73994.56</td>\n","      <td>122782.75</td>\n","      <td>303319.26</td>\n","      <td>110352.25</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>23</th>\n","      <td>67532.53</td>\n","      <td>105751.03</td>\n","      <td>304768.73</td>\n","      <td>108733.99</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>24</th>\n","      <td>77044.01</td>\n","      <td>99281.34</td>\n","      <td>140574.81</td>\n","      <td>108552.04</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>25</th>\n","      <td>64664.71</td>\n","      <td>139553.16</td>\n","      <td>137962.62</td>\n","      <td>107404.34</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>26</th>\n","      <td>75328.87</td>\n","      <td>144135.98</td>\n","      <td>134050.07</td>\n","      <td>105733.54</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>27</th>\n","      <td>72107.60</td>\n","      <td>127864.55</td>\n","      <td>353183.81</td>\n","      <td>105008.31</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>28</th>\n","      <td>66051.52</td>\n","      <td>182645.56</td>\n","      <td>118148.20</td>\n","      <td>103282.38</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>29</th>\n","      <td>65605.48</td>\n","      <td>153032.06</td>\n","      <td>107138.38</td>\n","      <td>101004.64</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>30</th>\n","      <td>61994.48</td>\n","      <td>115641.28</td>\n","      <td>91131.24</td>\n","      <td>99937.59</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>31</th>\n","      <td>61136.38</td>\n","      <td>152701.92</td>\n","      <td>88218.23</td>\n","      <td>97483.56</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>32</th>\n","      <td>63408.86</td>\n","      <td>129219.61</td>\n","      <td>46085.25</td>\n","      <td>97427.84</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>33</th>\n","      <td>55493.95</td>\n","      <td>103057.49</td>\n","      <td>214634.81</td>\n","      <td>96778.92</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>34</th>\n","      <td>46426.07</td>\n","      <td>157693.92</td>\n","      <td>210797.67</td>\n","      <td>96712.80</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>35</th>\n","      <td>46014.02</td>\n","      <td>85047.44</td>\n","      <td>205517.64</td>\n","      <td>96479.51</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>36</th>\n","      <td>28663.76</td>\n","      <td>127056.21</td>\n","      <td>201126.82</td>\n","      <td>90708.19</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>37</th>\n","      <td>44069.95</td>\n","      <td>51283.14</td>\n","      <td>197029.42</td>\n","      <td>89949.14</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>38</th>\n","      <td>20229.59</td>\n","      <td>65947.93</td>\n","      <td>185265.10</td>\n","      <td>81229.06</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>39</th>\n","      <td>38558.51</td>\n","      <td>82982.09</td>\n","      <td>174999.30</td>\n","      <td>81005.76</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>40</th>\n","      <td>28754.33</td>\n","      <td>118546.05</td>\n","      <td>172795.67</td>\n","      <td>78239.91</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>41</th>\n","      <td>27892.92</td>\n","      <td>84710.77</td>\n","      <td>164470.71</td>\n","      <td>77798.83</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>42</th>\n","      <td>23640.93</td>\n","      <td>96189.63</td>\n","      <td>148001.11</td>\n","      <td>71498.49</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>43</th>\n","      <td>15505.73</td>\n","      <td>127382.30</td>\n","      <td>35534.17</td>\n","      <td>69758.98</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>44</th>\n","      <td>22177.74</td>\n","      <td>154806.14</td>\n","      <td>28334.72</td>\n","      <td>65200.33</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>45</th>\n","      <td>1000.23</td>\n","      <td>124153.04</td>\n","      <td>1903.93</td>\n","      <td>64926.08</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>46</th>\n","      <td>1315.46</td>\n","      <td>115816.21</td>\n","      <td>297114.46</td>\n","      <td>49490.75</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>47</th>\n","      <td>0.00</td>\n","      <td>135426.92</td>\n","      <td>0.00</td>\n","      <td>42559.73</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>48</th>\n","      <td>542.05</td>\n","      <td>51743.15</td>\n","      <td>0.00</td>\n","      <td>35673.41</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>49</th>\n","      <td>0.00</td>\n","      <td>116983.80</td>\n","      <td>45173.06</td>\n","      <td>14681.40</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-34dad13a-07d4-4fa9-bff1-69d8061f6703')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 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Fazil","userId":"10693351885823441949"}},"outputId":"e2584448-5272-45db-c662-1b754c19717b"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['R&D Spend', 'Administration', 'Marketing Spend', 'Profit',\n","       'State_Florida', 'State_New York'],\n","      dtype='object')"]},"metadata":{},"execution_count":9}],"source":["dataset.columns"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"RyJG4R5oacF8"},"outputs":[],"source":["independent=dataset[['R&D Spend', 'Administration', 'Marketing Spend','State_Florida', 'State_New York']]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"nEd0AGdlacF8"},"outputs":[],"source":["dependent=dataset[[\"Profit\"]]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"0sxf2GBCacF8"},"outputs":[],"source":["from sklearn.model_selection import train_test_split\n","X_train,X_test,y_train,y_test=train_test_split(independent, dependent, test_size=0.30,random_state=0)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"StACsZa5acF8","executionInfo":{"status":"ok","timestamp":1690361890443,"user_tz":-330,"elapsed":12,"user":{"displayName":"Mohamed Fazil","userId":"10693351885823441949"}},"outputId":"69a5d171-3a90-4094-ea27-7f6f341b9421"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["    R&D Spend  Administration  Marketing Spend  State_Florida  State_New York\n","7   130298.13       145530.06        323876.68              1               0\n","14  119943.24       156547.42        256512.92              1               0\n","45    1000.23       124153.04          1903.93              0               1\n","48     542.05        51743.15             0.00              0               1\n","29   65605.48       153032.06        107138.38              0               1\n","15  114523.61       122616.84        261776.23              0               1\n","30   61994.48       115641.28         91131.24              1               0\n","32   63408.86       129219.61         46085.25              0               0\n","16   78013.11       121597.55        264346.06              0               0\n","42   23640.93        96189.63        148001.11              0               0\n","20   76253.86       113867.30        298664.47              0               0\n","43   15505.73       127382.30         35534.17              0               1\n","8   120542.52       148718.95        311613.29              0               1\n","13   91992.39       135495.07        252664.93              0               0\n","25   64664.71       139553.16        137962.62              0               0\n","5   131876.90        99814.71        362861.36              0               1\n","17   94657.16       145077.58        282574.31              0               1\n","40   28754.33       118546.05        172795.67              0               0\n","49       0.00       116983.80         45173.06              0               0\n","1   162597.70       151377.59        443898.53              0               0\n","12   93863.75       127320.38        249839.44              1               0\n","37   44069.95        51283.14        197029.42              0               0\n","24   77044.01        99281.34        140574.81              0               1\n","6   134615.46       147198.87        127716.82              0               0\n","23   67532.53       105751.03        304768.73              1               0\n","36   28663.76       127056.21        201126.82              1               0\n","21   78389.47       153773.43        299737.29              0               1\n","19   86419.70       153514.11             0.00              0               1\n","9   123334.88       108679.17        304981.62              0               0\n","39   38558.51        82982.09        174999.30              0               0\n","46    1315.46       115816.21        297114.46              1               0\n","3   144372.41       118671.85        383199.62              0               1\n","0   165349.20       136897.80        471784.10              0               1\n","47       0.00       135426.92             0.00              0               0\n","44   22177.74       154806.14         28334.72              0               0"],"text/html":["\n","\n","  <div id=\"df-e38e4ba5-fd2a-498f-9031-d06f7ef32f67\">\n","    <div class=\"colab-df-container\">\n","      <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>R&amp;D Spend</th>\n","      <th>Administration</th>\n","      <th>Marketing Spend</th>\n","      <th>State_Florida</th>\n","      <th>State_New York</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>7</th>\n","      <td>130298.13</td>\n","      <td>145530.06</td>\n","      <td>323876.68</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>119943.24</td>\n","      <td>156547.42</td>\n","      <td>256512.92</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>45</th>\n","      <td>1000.23</td>\n","      <td>124153.04</td>\n","      <td>1903.93</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>48</th>\n","      <td>542.05</td>\n","      <td>51743.15</td>\n","      <td>0.00</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>29</th>\n","      <td>65605.48</td>\n","      <td>153032.06</td>\n","      <td>107138.38</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>15</th>\n","      <td>114523.61</td>\n","      <td>122616.84</td>\n","      <td>261776.23</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>30</th>\n","      <td>61994.48</td>\n","      <td>115641.28</td>\n","      <td>91131.24</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>32</th>\n","      <td>63408.86</td>\n","      <td>129219.61</td>\n","      <td>46085.25</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>16</th>\n","      <td>78013.11</td>\n","      <td>121597.55</td>\n","      <td>264346.06</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>42</th>\n","      <td>23640.93</td>\n","      <td>96189.63</td>\n","      <td>148001.11</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>20</th>\n","      <td>76253.86</td>\n","      <td>113867.30</td>\n","      <td>298664.47</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>43</th>\n","      <td>15505.73</td>\n","      <td>127382.30</td>\n","      <td>35534.17</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>120542.52</td>\n","      <td>148718.95</td>\n","      <td>311613.29</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>91992.39</td>\n","      <td>135495.07</td>\n","      <td>252664.93</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>25</th>\n","      <td>64664.71</td>\n","      <td>139553.16</td>\n","      <td>137962.62</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>131876.90</td>\n","      <td>99814.71</td>\n","      <td>362861.36</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>17</th>\n","      <td>94657.16</td>\n","      <td>145077.58</td>\n","      <td>282574.31</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>40</th>\n","      <td>28754.33</td>\n","      <td>118546.05</td>\n","      <td>172795.67</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>49</th>\n","      <td>0.00</td>\n","      <td>116983.80</td>\n","      <td>45173.06</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>162597.70</td>\n","      <td>151377.59</td>\n","      <td>443898.53</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>93863.75</td>\n","      <td>127320.38</td>\n","      <td>249839.44</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>37</th>\n","      <td>44069.95</td>\n","      <td>51283.14</td>\n","      <td>197029.42</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>24</th>\n","      <td>77044.01</td>\n","      <td>99281.34</td>\n","      <td>140574.81</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>134615.46</td>\n","      <td>147198.87</td>\n","      <td>127716.82</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>23</th>\n","      <td>67532.53</td>\n","      <td>105751.03</td>\n","      <td>304768.73</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>36</th>\n","      <td>28663.76</td>\n","      <td>127056.21</td>\n","      <td>201126.82</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>21</th>\n","      <td>78389.47</td>\n","      <td>153773.43</td>\n","      <td>299737.29</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>19</th>\n","      <td>86419.70</td>\n","      <td>153514.11</td>\n","      <td>0.00</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>123334.88</td>\n","      <td>108679.17</td>\n","      <td>304981.62</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>39</th>\n","      <td>38558.51</td>\n","      <td>82982.09</td>\n","      <td>174999.30</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>46</th>\n","      <td>1315.46</td>\n","      <td>115816.21</td>\n","      <td>297114.46</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>144372.41</td>\n","      <td>118671.85</td>\n","      <td>383199.62</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>0</th>\n","      <td>165349.20</td>\n","      <td>136897.80</td>\n","      <td>471784.10</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>47</th>\n","      <td>0.00</td>\n","      <td>135426.92</td>\n","      <td>0.00</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>44</th>\n","      <td>22177.74</td>\n","      <td>154806.14</td>\n","      <td>28334.72</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e38e4ba5-fd2a-498f-9031-d06f7ef32f67')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 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'block' : 'none';\n","\n","        async function convertToInteractive(key) {\n","          const element = document.querySelector('#df-e38e4ba5-fd2a-498f-9031-d06f7ef32f67');\n","          const dataTable =\n","            await google.colab.kernel.invokeFunction('convertToInteractive',\n","                                                     [key], {});\n","          if (!dataTable) return;\n","\n","          const docLinkHtml = 'Like what you see? Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n"]},"metadata":{},"execution_count":13}],"source":["X_train"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"NZfoJrkNacF9"},"outputs":[],"source":["from sklearn.preprocessing import StandardScaler\n","sc=StandardScaler()\n","X_train=sc.fit_transform(X_train)\n","X_test=sc.transform(X_test)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"hqX1QrPZacF9","executionInfo":{"status":"ok","timestamp":1690361895683,"user_tz":-330,"elapsed":5,"user":{"displayName":"Mohamed Fazil","userId":"10693351885823441949"}},"outputId":"6a235a10-dde9-4629-dd08-add5405c586a"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[ 1.17644103,  0.84515251,  0.94354978,  2.        , -0.76870611],\n","       [ 0.96420324,  1.27283565,  0.42738817,  2.        , -0.76870611],\n","       [-1.47369826,  0.0153175 , -1.52350329, -0.5       ,  1.30088727],\n","       [-1.48308929, -2.79556363, -1.53809178, -0.5       ,  1.30088727],\n","       [-0.14952431,  1.13637282, -0.71716495, -0.5       ,  1.30088727],\n","       [ 0.85312042, -0.04431628,  0.46771725, -0.5       ,  1.30088727],\n","       [-0.22353674, -0.3151007 , -0.83981652,  2.        , -0.76870611],\n","       [-0.19454707,  0.21199679, -1.18497259, -0.5       , -0.76870611],\n","       [ 0.10478723, -0.08388412,  0.48740807, -0.5       , -0.76870611],\n","       [-1.0096458 , -1.07019473, -0.4040623 , -0.5       , -0.76870611],\n","       [ 0.06872897, -0.38396487,  0.75036616, -0.5       , -0.76870611],\n","       [-1.17638797,  0.14067421, -1.26581817, -0.5       ,  1.30088727],\n","       [ 0.97648631,  0.9689421 ,  0.84958395, -0.5       ,  1.30088727],\n","       [ 0.39131191,  0.45560401,  0.3979037 , -0.5       , -0.76870611],\n","       [-0.16880669,  0.6131351 , -0.48098026, -0.5       , -0.76870611],\n","       [ 1.2088001 , -0.92947267,  1.24226224, -0.5       ,  1.30088727],\n","       [ 0.44593006,  0.82758768,  0.62707846, -0.5       ,  1.30088727],\n","       [-0.90483959, -0.20234037, -0.21407884, -0.5       , -0.76870611],\n","       [-1.49419935, -0.26298539, -1.19196207, -0.5       , -0.76870611],\n","       [ 1.83846539,  1.07214791,  1.86319367, -0.5       , -0.76870611],\n","       [ 0.42966802,  0.13827054,  0.37625394,  2.        , -0.76870611],\n","       [-0.59092478, -2.81342077, -0.02839248, -0.5       , -0.76870611],\n","       [ 0.08492419, -0.95017758, -0.46096486, -0.5       ,  1.30088727],\n","       [ 1.26493068,  0.90993408, -0.55948669, -0.5       , -0.76870611],\n","       [-0.11002675, -0.69903054,  0.79713886,  2.        , -0.76870611],\n","       [-0.90669595,  0.12801572,  0.00300304,  2.        , -0.76870611],\n","       [ 0.11250125,  1.16515207,  0.75858643, -0.5       ,  1.30088727],\n","       [ 0.27709192,  1.15508553, -1.53809178, -0.5       ,  1.30088727],\n","       [ 1.03371959, -0.585363  ,  0.79877008, -0.5       , -0.76870611],\n","       [-0.70388936, -1.58289852, -0.19719396, -0.5       , -0.76870611],\n","       [-1.46723718, -0.30831009,  0.73848951,  2.        , -0.76870611],\n","       [ 1.46491286, -0.19745694,  1.39810017, -0.5       ,  1.30088727],\n","       [ 1.89486118,  0.51005662,  2.07686138, -0.5       ,  1.30088727],\n","       [-1.49419935,  0.4529585 , -1.53809178, -0.5       , -0.76870611],\n","       [-1.0396359 ,  1.20524087, -1.32098255, -0.5       , -0.76870611]])"]},"metadata":{},"execution_count":15}],"source":["X_train"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"kj3-IYyCacF9"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"metadata":{"scrolled":false,"colab":{"base_uri":"https://localhost:8080/","height":129},"id":"OmhB8pMfacF9","executionInfo":{"status":"ok","timestamp":1690361897435,"user_tz":-330,"elapsed":10,"user":{"displayName":"Mohamed Fazil","userId":"10693351885823441949"}},"outputId":"b0690aef-99c8-4ae4-925e-b6c8e818cc90"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/sklearn/utils/validation.py:1143: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n","  y = column_or_1d(y, warn=True)\n"]},{"output_type":"execute_result","data":{"text/plain":["SVR(C=1000)"],"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>SVR(C=1000)</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\">SVR</label><div class=\"sk-toggleable__content\"><pre>SVR(C=1000)</pre></div></div></div></div></div>"]},"metadata":{},"execution_count":16}],"source":["from sklearn.svm import SVR\n","regressor=SVR(kernel=\"rbf\",C=1000)\n","regressor.fit(X_train,y_train)\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"kAY9w0NLacF9","executionInfo":{"status":"ok","timestamp":1690441487771,"user_tz":-330,"elapsed":5,"user":{"displayName":"Krishna Vardhan","userId":"17279961073454177505"}}},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"0fWbXEa1acF9","executionInfo":{"status":"ok","timestamp":1690361898838,"user_tz":-330,"elapsed":4,"user":{"displayName":"Mohamed Fazil","userId":"10693351885823441949"}},"outputId":"f34d3c97-5842-48ce-b6cb-c93f7a3daf14"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([108599.21691873])"]},"metadata":{},"execution_count":17}],"source":["\n","1regressor.intercept_"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"YwxorH6HacF9","executionInfo":{"status":"ok","timestamp":1690361899435,"user_tz":-330,"elapsed":8,"user":{"displayName":"Mohamed Fazil","userId":"10693351885823441949"}},"outputId":"5df9099d-9a35-47d6-fe48-ba1c64f724af"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([35], dtype=int32)"]},"metadata":{},"execution_count":18}],"source":["regressor.n_support_"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"mzwOWb6oacF9","executionInfo":{"status":"ok","timestamp":1690361902050,"user_tz":-330,"elapsed":2,"user":{"displayName":"Mohamed Fazil","userId":"10693351885823441949"}},"outputId":"dd1fcd53-dbeb-411e-d272-6e378e512c25"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n","       17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n","       34], dtype=int32)"]},"metadata":{},"execution_count":19}],"source":["regressor.support_"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"xtMjMNbXacF9"},"outputs":[],"source":["y_pred=regressor.predict(X_test)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"451kVyuAacF-"},"outputs":[],"source":["from sklearn.metrics import r2_score\n","r_score=r2_score(y_test,y_pred)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"nw3_U6O6acF-","executionInfo":{"status":"ok","timestamp":1690361906223,"user_tz":-330,"elapsed":4,"user":{"displayName":"Mohamed Fazil","userId":"10693351885823441949"}},"outputId":"79ed0ab3-8c92-403c-9cb6-2abbce161aca"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.0067683444800727965"]},"metadata":{},"execution_count":22}],"source":["r_score"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"-14NhHbIacF-"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"metadata":{"id":"xAXmvgv8acF-"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"metadata":{"id":"eLTknnd-acF-"},"outputs":[],"source":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.4"},"colab":{"provenance":[]}},"nbformat":4,"nbformat_minor":0}