Leukemia Feature Selection Task B.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Leukemia Feature Selection Task B.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true,"authorship_tag":"ABX9TyNCRGqJxEmj2j9C5CYutJXb"},"kernelspec":{"display_name":"Python 3","name":"python3"}},"cells":[{"cell_type":"code","metadata":{"id":"XRW276KYgn1z","executionInfo":{"status":"ok","timestamp":1602970550151,"user_tz":-330,"elapsed":8837,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"c32af67e-d1fb-43ee-9c57-314c0ef1d40b","colab":{"base_uri":"https://localhost:8080/","height":254}},"source":["!pip install -U scikit-learn"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Collecting scikit-learn\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/5c/a1/273def87037a7fb010512bbc5901c31cfddfca8080bc63b42b26e3cc55b3/scikit_learn-0.23.2-cp36-cp36m-manylinux1_x86_64.whl (6.8MB)\n","\u001b[K     |████████████████████████████████| 6.8MB 2.7MB/s \n","\u001b[?25hCollecting threadpoolctl>=2.0.0\n","  Downloading https://files.pythonhosted.org/packages/f7/12/ec3f2e203afa394a149911729357aa48affc59c20e2c1c8297a60f33f133/threadpoolctl-2.1.0-py3-none-any.whl\n","Requirement already satisfied, skipping upgrade: scipy>=0.19.1 in /usr/local/lib/python3.6/dist-packages (from scikit-learn) (1.4.1)\n","Requirement already satisfied, skipping upgrade: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from scikit-learn) (0.16.0)\n","Requirement already satisfied, skipping upgrade: numpy>=1.13.3 in /usr/local/lib/python3.6/dist-packages (from scikit-learn) (1.18.5)\n","Installing collected packages: threadpoolctl, scikit-learn\n","  Found existing installation: scikit-learn 0.22.2.post1\n","    Uninstalling scikit-learn-0.22.2.post1:\n","      Successfully uninstalled scikit-learn-0.22.2.post1\n","Successfully installed scikit-learn-0.23.2 threadpoolctl-2.1.0\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"0V2ggHzhMII-","executionInfo":{"status":"ok","timestamp":1602970550152,"user_tz":-330,"elapsed":8833,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["#Importing Libraries\n","import numpy as np\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","import re\n","from sklearn.model_selection import train_test_split\n","from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\n","from sklearn.metrics import mutual_info_score\n","from sklearn.neighbors import NearestNeighbors\n","from sklearn.preprocessing import scale\n","from sklearn.utils import check_random_state\n","from sklearn.utils.fixes import _astype_copy_false\n","from sklearn.utils.validation import check_array, check_X_y\n","from sklearn.utils.validation import _deprecate_positional_args\n","from sklearn.utils.multiclass import check_classification_targets\n","from sklearn.metrics import accuracy_score\n","from sklearn.metrics import f1_score\n","from sklearn.metrics import confusion_matrix\n","from sklearn import svm\n","from scipy import special, stats\n","from scipy.sparse import issparse\n","from sklearn.base import BaseEstimator\n","from sklearn.preprocessing import LabelBinarizer\n","from sklearn.utils import (as_float_array, check_array, check_X_y, safe_sqr,safe_mask)\n","from sklearn.utils.extmath import safe_sparse_dot, row_norms\n","from sklearn.utils.validation import check_is_fitted\n","from sklearn.utils.validation import _deprecate_positional_args\n","from sklearn.feature_selection._base import SelectorMixin\n","from sklearn.metrics import roc_auc_score\n","from scipy.sparse import issparse\n","from scipy.special import digamma\n","import scipy.stats as stats\n","from subprocess import check_output\n","#from mlxtend.feature_selection import SequentialFeatureSelector as SFS\n","import warnings\n","warnings.filterwarnings('ignore')\n","%matplotlib inline"],"execution_count":2,"outputs":[]},{"cell_type":"code","metadata":{"id":"IhmnO4Y4M3_q","executionInfo":{"status":"ok","timestamp":1602970573634,"user_tz":-330,"elapsed":1553,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"cf2286d5-9577-4f91-96d3-35cbbf5b3059","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["#importing dataset\n","df = pd.read_csv('leukemia.tab', delimiter='\\t')\n","df.shape"],"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(75, 5148)"]},"metadata":{"tags":[]},"execution_count":3}]},{"cell_type":"code","metadata":{"id":"XwbZnDMKNZWX","executionInfo":{"status":"ok","timestamp":1602970573638,"user_tz":-330,"elapsed":1263,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["df=df.dropna().loc[1:,:]"],"execution_count":4,"outputs":[]},{"cell_type":"code","metadata":{"id":"62_oXKSlNuek","executionInfo":{"status":"ok","timestamp":1602970574958,"user_tz":-330,"elapsed":1971,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"85cd85e5-5f91-4944-8386-e77ebf181067","colab":{"base_uri":"https://localhost:8080/","height":279}},"source":["X = df.drop(['gene'], axis=1)\n","X.head()"],"execution_count":5,"outputs":[{"output_type":"execute_result","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>AFFX-BioC-5_at</th>\n","      <th>hum_alu_at</th>\n","      <th>AFFX-DapX-M_at</th>\n","      <th>AFFX-LysX-5_at</th>\n","      <th>AFFX-HUMISGF3A/M97935_MA_at</th>\n","      <th>AFFX-HUMISGF3A/M97935_MB_at</th>\n","      <th>AFFX-HUMISGF3A/M97935_3_at</th>\n","      <th>AFFX-HUMRGE/M10098_5_at</th>\n","      <th>AFFX-HUMRGE/M10098_M_at</th>\n","      <th>AFFX-HUMRGE/M10098_3_at</th>\n","      <th>AFFX-HUMGAPDH/M33197_5_at</th>\n","      <th>AFFX-HUMGAPDH/M33197_M_at</th>\n","      <th>AFFX-HUMGAPDH/M33197_3_at</th>\n","      <th>AFFX-HSAC07/X00351_5_at</th>\n","      <th>AFFX-HSAC07/X00351_M_at</th>\n","      <th>AFFX-HSAC07/X00351_3_at</th>\n","      <th>AFFX-HUMTFRR/M11507_5_at</th>\n","      <th>AFFX-HUMTFRR/M11507_M_at</th>\n","      <th>AFFX-HUMTFRR/M11507_3_at</th>\n","      <th>AFFX-M27830_5_at</th>\n","      <th>AFFX-M27830_M_at</th>\n","      <th>AFFX-HSAC07/X00351_3_st</th>\n","      <th>AFFX-HUMGAPDH/M33197_M_st</th>\n","      <th>AFFX-HUMGAPDH/M33197_3_st</th>\n","      <th>AFFX-HSAC07/X00351_M_st</th>\n","      <th>A28102_at</th>\n","      <th>AB000114_at</th>\n","      <th>AB000115_at</th>\n","      <th>AB000220_at</th>\n","      <th>AB000409_at</th>\n","      <th>AB000449_at</th>\n","      <th>AB000450_at</th>\n","      <th>AB000460_at</th>\n","      <th>AB000462_at</th>\n","      <th>AB000464_at</th>\n","      <th>AB000467_at</th>\n","      <th>AB000468_at</th>\n","      <th>AB000584_at</th>\n","      <th>AB000905_at</th>\n","      <th>AB001106_at</th>\n","      <th>...</th>\n","      <th>U10690_f_at</th>\n","      <th>U22029_f_at</th>\n","      <th>U49974_f_at</th>\n","      <th>U65918_f_at</th>\n","      <th>V00532_rna1_f_at</th>\n","      <th>V00533_rna1_f_at</th>\n","      <th>V01516_f_at</th>\n","      <th>X13930_f_at</th>\n","      <th>X53065_f_at</th>\n","      <th>X64177_f_at</th>\n","      <th>X67491_f_at</th>\n","      <th>X71345_f_at</th>\n","      <th>X97444_f_at</th>\n","      <th>Z80780_f_at</th>\n","      <th>X00351_f_at</th>\n","      <th>X01677_f_at</th>\n","      <th>M31667_f_at</th>\n","      <th>L41268_f_at</th>\n","      <th>X99479_f_at</th>\n","      <th>HG658-HT658_f_at</th>\n","      <th>M94880_f_at</th>\n","      <th>X03068_f_at</th>\n","      <th>U87593_f_at</th>\n","      <th>U88902_cds1_f_at</th>\n","      <th>AC002076_cds2_at</th>\n","      <th>D64015_at</th>\n","      <th>L10717_at</th>\n","      <th>L78833_cds4_at</th>\n","      <th>M13981_at</th>\n","      <th>M21064_at</th>\n","      <th>M93143_at</th>\n","      <th>U29175_at</th>\n","      <th>U48730_at</th>\n","      <th>U58516_at</th>\n","      <th>X06956_at</th>\n","      <th>X83863_at</th>\n","      <th>Z17240_at</th>\n","      <th>L49218_f_at</th>\n","      <th>M71243_f_at</th>\n","      <th>Z78285_f_at</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2</th>\n","      <td>88</td>\n","      <td>15091</td>\n","      <td>311</td>\n","      <td>21</td>\n","      <td>-13</td>\n","      <td>215</td>\n","      <td>797</td>\n","      <td>14538</td>\n","      <td>9738</td>\n","      <td>8529</td>\n","      <td>15076</td>\n","      <td>11126</td>\n","      <td>17782</td>\n","      <td>16287</td>\n","      <td>18727</td>\n","      <td>15774</td>\n","      <td>264</td>\n","      <td>70</td>\n","      <td>298</td>\n","      <td>6750</td>\n","      <td>6559</td>\n","      <td>2982</td>\n","      <td>132</td>\n","      <td>546</td>\n","      <td>336</td>\n","      <td>151</td>\n","      <td>72</td>\n","      <td>281</td>\n","      <td>36</td>\n","      <td>-299</td>\n","      <td>57</td>\n","      <td>186</td>\n","      <td>1647</td>\n","      <td>137</td>\n","      <td>803</td>\n","      <td>-632</td>\n","      <td>378</td>\n","      <td>-26</td>\n","      <td>155</td>\n","      <td>355</td>\n","      <td>...</td>\n","      <td>246</td>\n","      <td>26</td>\n","      <td>63</td>\n","      <td>60</td>\n","      <td>-20</td>\n","      <td>-30</td>\n","      <td>488</td>\n","      <td>504</td>\n","      <td>391</td>\n","      <td>-763</td>\n","      <td>172</td>\n","      <td>149</td>\n","      <td>341</td>\n","      <td>788</td>\n","      <td>21210</td>\n","      <td>13771</td>\n","      <td>598</td>\n","      <td>396</td>\n","      <td>245</td>\n","      <td>14476</td>\n","      <td>10882</td>\n","      <td>2762</td>\n","      <td>-67</td>\n","      <td>346</td>\n","      <td>-68</td>\n","      <td>229</td>\n","      <td>108</td>\n","      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<td>250</td>\n","      <td>43</td>\n","      <td>-103</td>\n","      <td>169</td>\n","      <td>219</td>\n","      <td>2043</td>\n","      <td>188</td>\n","      <td>756</td>\n","      <td>-700</td>\n","      <td>249</td>\n","      <td>-242</td>\n","      <td>131</td>\n","      <td>431</td>\n","      <td>...</td>\n","      <td>394</td>\n","      <td>-83</td>\n","      <td>153</td>\n","      <td>18</td>\n","      <td>3</td>\n","      <td>-135</td>\n","      <td>518</td>\n","      <td>440</td>\n","      <td>200</td>\n","      <td>51</td>\n","      <td>154</td>\n","      <td>418</td>\n","      <td>433</td>\n","      <td>736</td>\n","      <td>21059</td>\n","      <td>15097</td>\n","      <td>563</td>\n","      <td>171</td>\n","      <td>-149</td>\n","      <td>13686</td>\n","      <td>11789</td>\n","      <td>1567</td>\n","      <td>-88</td>\n","      <td>290</td>\n","      <td>14</td>\n","      <td>194</td>\n","      <td>303</td>\n","      <td>214</td>\n","      <td>-28</td>\n","      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<td>315</td>\n","      <td>1199</td>\n","      <td>168</td>\n","      <td>1138</td>\n","      <td>777</td>\n","      <td>41</td>\n","      <td>228</td>\n","      <td>-41</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>12</td>\n","      <td>15763</td>\n","      <td>268</td>\n","      <td>43</td>\n","      <td>-148</td>\n","      <td>155</td>\n","      <td>415</td>\n","      <td>4850</td>\n","      <td>2293</td>\n","      <td>2569</td>\n","      <td>14920</td>\n","      <td>11439</td>\n","      <td>17633</td>\n","      <td>15770</td>\n","      <td>18773</td>\n","      <td>14245</td>\n","      <td>183</td>\n","      <td>-54</td>\n","      <td>260</td>\n","      <td>3058</td>\n","      <td>2442</td>\n","      <td>1731</td>\n","      <td>-76</td>\n","      <td>327</td>\n","      <td>511</td>\n","      <td>484</td>\n","      <td>61</td>\n","      <td>118</td>\n","      <td>39</td>\n","      <td>-11</td>\n","      <td>274</td>\n","      <td>245</td>\n","      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<td>174</td>\n","      <td>627</td>\n","      <td>170</td>\n","      <td>-50</td>\n","      <td>126</td>\n","      <td>-91</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>168</td>\n","      <td>18128</td>\n","      <td>118</td>\n","      <td>-8</td>\n","      <td>-55</td>\n","      <td>122</td>\n","      <td>483</td>\n","      <td>1284</td>\n","      <td>2731</td>\n","      <td>316</td>\n","      <td>14653</td>\n","      <td>15030</td>\n","      <td>17384</td>\n","      <td>16386</td>\n","      <td>19091</td>\n","      <td>18323</td>\n","      <td>291</td>\n","      <td>78</td>\n","      <td>287</td>\n","      <td>1130</td>\n","      <td>1056</td>\n","      <td>728</td>\n","      <td>89</td>\n","      <td>120</td>\n","      <td>65</td>\n","      <td>118</td>\n","      <td>16</td>\n","      <td>197</td>\n","      <td>39</td>\n","      <td>237</td>\n","      <td>311</td>\n","      <td>186</td>\n","      <td>1608</td>\n","      <td>204</td>\n","      <td>322</td>\n","      <td>-254</td>\n","      <td>554</td>\n","      <td>16</td>\n","      <td>45</td>\n","      <td>569</td>\n","      <td>...</td>\n","      <td>139</td>\n","      <td>45</td>\n","      <td>-29</td>\n","      <td>23</td>\n","      <td>-20</td>\n","      <td>-104</td>\n","      <td>325</td>\n","      <td>299</td>\n","      <td>162</td>\n","      <td>-56</td>\n","      <td>279</td>\n","      <td>183</td>\n","      <td>259</td>\n","      <td>605</td>\n","      <td>18530</td>\n","      <td>15619</td>\n","      <td>65</td>\n","      <td>122</td>\n","      <td>126</td>\n","      <td>8443</td>\n","      <td>8512</td>\n","      <td>1503</td>\n","      <td>29</td>\n","      <td>159</td>\n","      <td>18</td>\n","      <td>71</td>\n","      <td>44</td>\n","      <td>159</td>\n","      <td>71</td>\n","      <td>134</td>\n","      <td>178</td>\n","      <td>626</td>\n","      <td>156</td>\n","      <td>649</td>\n","      <td>504</td>\n","      <td>250</td>\n","      <td>314</td>\n","      <td>14</td>\n","      <td>56</td>\n","      <td>-25</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 5147 columns</p>\n","</div>"],"text/plain":["  AFFX-BioC-5_at hum_alu_at AFFX-DapX-M_at  ... L49218_f_at M71243_f_at Z78285_f_at\n","2             88      15091            311  ...          36         191         -37\n","3            283      11038            134  ...          11          76         -14\n","4            309      16692            378  ...          41         228         -41\n","5             12      15763            268  ...         -50         126         -91\n","6            168      18128            118  ...          14          56         -25\n","\n","[5 rows x 5147 columns]"]},"metadata":{"tags":[]},"execution_count":5}]},{"cell_type":"code","metadata":{"id":"3RyMVKS9OdXH","executionInfo":{"status":"ok","timestamp":1602970591306,"user_tz":-330,"elapsed":1232,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"dd7ae04f-1da5-464f-fa6e-6c4bc61f04b6","colab":{"base_uri":"https://localhost:8080/","height":117}},"source":["# Mapping genes into integers\n","y = df['gene']\n","y=y.map({'ALL': 1, 'AML': 0})\n","y.head()"],"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["2    1\n","3    1\n","4    1\n","5    1\n","6    1\n","Name: gene, dtype: int64"]},"metadata":{"tags":[]},"execution_count":6}]},{"cell_type":"code","metadata":{"id":"RnLB1lnpOiCl","executionInfo":{"status":"ok","timestamp":1602970592825,"user_tz":-330,"elapsed":913,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"00cd1eb9-e808-465a-ee91-1712e0e06980","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["#Train test split\n","X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=101)\n","X_train.shape, y_train.shape, X_test.shape, y_test.shape"],"execution_count":7,"outputs":[{"output_type":"execute_result","data":{"text/plain":["((57, 5147), (57,), (15, 5147), (15,))"]},"metadata":{"tags":[]},"execution_count":7}]},{"cell_type":"code","metadata":{"id":"-rQnYX-oIbol","executionInfo":{"status":"ok","timestamp":1602970594611,"user_tz":-330,"elapsed":1459,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["from sklearn.feature_selection import VarianceThreshold\n","from sklearn.feature_selection import SelectKBest, SelectPercentile\n","constant_filter = VarianceThreshold(threshold=0.01)\n","constant_filter.fit(X_train)\n","X_train_filter = constant_filter.transform(X_train)\n","X_test_filter = constant_filter.transform(X_test)"],"execution_count":8,"outputs":[]},{"cell_type":"code","metadata":{"id":"OxG02Ab6Imzt","executionInfo":{"status":"ok","timestamp":1602970594612,"user_tz":-330,"elapsed":1147,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["X_train_T = X_train_filter.T\n","X_test_T = X_test_filter.T\n","X_train_T = pd.DataFrame(X_train_T)\n","X_test_T = pd.DataFrame(X_test_T)"],"execution_count":9,"outputs":[]},{"cell_type":"code","metadata":{"id":"iHg513MtIy_Y","executionInfo":{"status":"ok","timestamp":1602970595352,"user_tz":-330,"elapsed":1501,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"3746b88f-41b8-4c56-ddeb-bc412682a6f7","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["X_train_T.duplicated().sum()"],"execution_count":10,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0"]},"metadata":{"tags":[]},"execution_count":10}]},{"cell_type":"code","metadata":{"id":"1hFLQHoGI3dQ","executionInfo":{"status":"ok","timestamp":1602970595353,"user_tz":-330,"elapsed":1261,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["duplicated_features = X_train_T.duplicated()"],"execution_count":11,"outputs":[]},{"cell_type":"code","metadata":{"id":"6MPtXEwvI8kU","executionInfo":{"status":"ok","timestamp":1602970596080,"user_tz":-330,"elapsed":1724,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"e826dce9-b389-49e5-c783-adde492860a7","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["features_to_keep = [not index for index in duplicated_features]\n","X_train_unique = X_train_T[features_to_keep].T\n","X_test_unique = X_test_T[features_to_keep].T\n","X_train_unique.shape, X_test_unique.shape"],"execution_count":12,"outputs":[{"output_type":"execute_result","data":{"text/plain":["((57, 5147), (15, 5147))"]},"metadata":{"tags":[]},"execution_count":12}]},{"cell_type":"code","metadata":{"id":"L6GkgI31VDzg","executionInfo":{"status":"ok","timestamp":1602970596929,"user_tz":-330,"elapsed":2361,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["#Function for KNN Classifier C1\n","from sklearn.neighbors import KNeighborsClassifier\n","def run_knn(X_train, X_test, y_train, y_test):\n","    c1 =KNeighborsClassifier(n_neighbors=3)\n","    c1.fit(X_train, y_train)\n","    y_pred = c1.predict(X_train)\n","    y_test_pred=c1.predict(X_test)\n","    print('Training 80% data report::')\n","    print('Accuracy Score: ')\n","    print(accuracy_score(y_train, y_pred))\n","    print('F1-Score: ')\n","    print(f1_score(y_train, y_pred))\n","    print('Confusion Matrix: ')\n","    print(confusion_matrix(y_train, y_pred))\n","    print('Testing 20% data report::')\n","    print('Accuracy Score: ')\n","    print(accuracy_score(y_test, y_test_pred))\n","    print('F1-Score: ')\n","    print(f1_score(y_test, y_test_pred))\n","    print('Confusion Matrix: ')\n","    print(confusion_matrix(y_test, y_test_pred))\n"],"execution_count":13,"outputs":[]},{"cell_type":"code","metadata":{"id":"a8xhZQbZKfB0","executionInfo":{"status":"ok","timestamp":1602970596930,"user_tz":-330,"elapsed":2147,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["#Function for SVM Classifier C2\n","def run_svm(X_train, X_test, y_train, y_test):\n","    c2 =svm.SVC()\n","    c2.fit(X_train, y_train)\n","    y_pred = c2.predict(X_train)\n","    y_test_pred=c2.predict(X_test)\n","    print('Training 80% data report::')\n","    print('Accuracy Score: ')\n","    print(accuracy_score(y_train, y_pred))\n","    print('F1-Score: ')\n","    print(f1_score(y_train, y_pred))\n","    print('Confusion Matrix: ')\n","    print(confusion_matrix(y_train, y_pred))\n","    print('Testing 20% data report::')\n","    print('Accuracy Score: ')\n","    print(accuracy_score(y_test, y_test_pred))\n","    print('F1-Score: ')\n","    print(f1_score(y_test, y_test_pred))\n","    print('Confusion Matrix: ')\n","    print(confusion_matrix(y_test, y_test_pred))"],"execution_count":14,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"C30WJF8gWfDs"},"source":["## Functions of Mutual Information based feature selection(f1), F- Classifier(f2) and T-Test(f3)"]},{"cell_type":"code","metadata":{"id":"RcPWgG8dZCwa","executionInfo":{"status":"ok","timestamp":1602970596931,"user_tz":-330,"elapsed":1817,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["# Functions of Mutual information\n","def _compute_mi(x, y, n_neighbors=3):\n","        return mutual_info_score(x, y)\n","\n","def _iterate_columns(X, columns=None):\n","    if columns is None:\n","        columns = range(X.shape[1])\n","\n","    if issparse(X):\n","        for i in columns:\n","            x = np.zeros(X.shape[0])\n","            start_ptr, end_ptr = X.indptr[i], X.indptr[i + 1]\n","            x[X.indices[start_ptr:end_ptr]] = X.data[start_ptr:end_ptr]\n","            yield x\n","    else:\n","        for i in columns:\n","            yield X[:, i]\n","\n","\n","def _estimate_mi(X, y,n_neighbors=3):\n","    X, y = check_X_y(X, y, accept_sparse='csc')\n","    n_samples, n_features = X.shape\n","    discrete_features = issparse(X)\n","    discrete_mask = np.empty(n_features, dtype=bool)\n","    discrete_mask.fill(discrete_features)\n","    \n","    mi = [_compute_mi(x, y, n_neighbors) for\n","          x, discrete_feature in zip(_iterate_columns(X), discrete_mask)]\n","\n","    return np.array(mi)\n","\n","def mutual_info_classifier(X, y, n_neighbors=3,):\n","    check_classification_targets(y)\n","    return _estimate_mi(X, y, n_neighbors)"],"execution_count":15,"outputs":[]},{"cell_type":"code","metadata":{"id":"7rGumBvIcMaf","executionInfo":{"status":"ok","timestamp":1602970596932,"user_tz":-330,"elapsed":1644,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["#Functions for F classifier \n","def f_oneway(*args):\n","    n_classes = len(args)\n","    args = [as_float_array(a) for a in args]\n","    n_samples_per_class = np.array([a.shape[0] for a in args])\n","    n_samples = np.sum(n_samples_per_class)\n","    ss_alldata = sum(safe_sqr(a).sum(axis=0) for a in args)\n","    sums_args = [np.asarray(a.sum(axis=0)) for a in args]\n","    square_of_sums_alldata = sum(sums_args) ** 2\n","    square_of_sums_args = [s ** 2 for s in sums_args]\n","    sstot = ss_alldata - square_of_sums_alldata / float(n_samples)\n","    ssbn = 0.\n","    for k, _ in enumerate(args):\n","        ssbn += square_of_sums_args[k] / n_samples_per_class[k]\n","    ssbn -= square_of_sums_alldata / float(n_samples)\n","    sswn = sstot - ssbn\n","    dfbn = n_classes - 1\n","    dfwn = n_samples - n_classes\n","    msb = ssbn / float(dfbn)\n","    msw = sswn / float(dfwn)\n","    constant_features_idx = np.where(msw == 0.)[0]\n","    f = msb / msw #High variance upon low variance \n","    # flatten matrix to vector in sparse case\n","    f = np.asarray(f).ravel()\n","    prob = special.fdtrc(dfbn, dfwn, f)\n","    return f, prob\n","\n","\n","def f_classif(X, y):\n","    X, y = check_X_y(X, y, accept_sparse=['csr', 'csc', 'coo'])\n","    args = [X[safe_mask(X, y == k)] for k in np.unique(y)]\n","    return f_oneway(*args)"],"execution_count":16,"outputs":[]},{"cell_type":"code","metadata":{"id":"XvJia5UPdsxb","executionInfo":{"status":"ok","timestamp":1602970597761,"user_tz":-330,"elapsed":2293,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["#Functions for  t-test \n","import math\n","def t_oneway(*args):\n","    n_classes = len(args)\n","    args = [as_float_array(a) for a in args]\n","    n_samples_per_class = np.array([a.shape[0] for a in args])\n","    n_samples = np.sum(n_samples_per_class)\n","    ss_alldata = sum(safe_sqr(a).sum(axis=0) for a in args)\n","    sums_args = [np.asarray(a.sum(axis=0)) for a in args]\n","    square_of_sums_alldata = sum(sums_args) ** 2\n","    square_of_sums_args = [s ** 2 for s in sums_args]\n","    sstot = ss_alldata - square_of_sums_alldata / float(n_samples)\n","    ssbn = 0.\n","    for k, _ in enumerate(args):\n","        ssbn += square_of_sums_args[k] / n_samples_per_class[k]\n","    ssbn -= square_of_sums_alldata / float(n_samples)\n","    sswn = sstot - ssbn\n","    dfbn = n_classes - 1\n","    dfwn = n_samples - n_classes\n","    msb = ssbn / float(dfbn)\n","    msw = sswn / float(dfwn)\n","    constant_features_idx = np.where(msw == 0.)[0]\n","    t = (ssbn-sswn)**2/ (msb+msw) #Taking sqrt of t value instead of absolute as t due to limitation of numpy. t^2= (absolute differences of means/sum of variances)^2\n","    # flatten matrix to vector in sparse case\n","    t = np.asarray(t).ravel()\n","    prob = special.fdtrc(dfbn, dfwn, t)\n","    return t, prob\n","\n","\n","def t_test(X, y):\n","    X, y = check_X_y(X, y, accept_sparse=['csr', 'csc', 'coo'])\n","    args = [X[safe_mask(X, y == k)] for k in np.unique(y)]\n","    return t_oneway(*args)"],"execution_count":17,"outputs":[]},{"cell_type":"code","metadata":{"id":"rz0Y686MI_sp","executionInfo":{"status":"ok","timestamp":1602970602885,"user_tz":-330,"elapsed":7226,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"391ebbd1-d0b4-4fc9-f28d-0b6c7ec29e66","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["mi = mutual_info_classifier(X_train_unique, y_train) \n","len(mi)"],"execution_count":18,"outputs":[{"output_type":"execute_result","data":{"text/plain":["5147"]},"metadata":{"tags":[]},"execution_count":18}]},{"cell_type":"code","metadata":{"id":"2xJEzvEWJCe7","executionInfo":{"status":"ok","timestamp":1602970602887,"user_tz":-330,"elapsed":7048,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"d5c5ddc5-b396-4324-8782-570f58bebcc7","colab":{"base_uri":"https://localhost:8080/","height":50}},"source":["mi[: 10]"],"execution_count":19,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([0.62366701, 0.64798797, 0.5750251 , 0.55666552, 0.62366701,\n","       0.55070415, 0.59934606, 0.59934606, 0.62366701, 0.62366701])"]},"metadata":{"tags":[]},"execution_count":19}]},{"cell_type":"code","metadata":{"id":"wHwnV5i9JJ-H","executionInfo":{"status":"ok","timestamp":1602970602888,"user_tz":-330,"elapsed":6892,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["mi = pd.Series(mi)\n","mi.index = X_train_unique.columns"],"execution_count":20,"outputs":[]},{"cell_type":"code","metadata":{"id":"xnPS468gJME8","executionInfo":{"status":"ok","timestamp":1602970602889,"user_tz":-330,"elapsed":6741,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["mi.sort_values(ascending=False, inplace = True)"],"execution_count":21,"outputs":[]},{"cell_type":"code","metadata":{"id":"igeS4hNAi2UA","executionInfo":{"status":"ok","timestamp":1602970602891,"user_tz":-330,"elapsed":6543,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"8f9a22ac-240a-4c8c-9507-9827de381481","colab":{"base_uri":"https://localhost:8080/","height":84}},"source":["mi.index"],"execution_count":22,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Int64Index([2225,  580, 3972,  845, 3975, 3976, 1831, 2704,  843,  840,\n","            ...\n","            3990, 1919,  292, 2565, 3216, 3346, 3154, 3623, 3615, 3328],\n","           dtype='int64', length=5147)"]},"metadata":{"tags":[]},"execution_count":22}]},{"cell_type":"markdown","metadata":{"id":"QPpPD5u6jmgM"},"source":["### Selecting N/3 Features of f1"]},{"cell_type":"code","metadata":{"id":"eeknLAcfJQ6y","executionInfo":{"status":"ok","timestamp":1602970608075,"user_tz":-330,"elapsed":11374,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"dffe34e9-bebc-4f62-d0e2-7f5e72199d0b","colab":{"base_uri":"https://localhost:8080/","height":84}},"source":["sel = SelectKBest(mutual_info_classifier, k=int(len(mi.index)/3*0.15)).fit(X_train_unique, y_train)#0.15 is multiplied to take 15%of the total features\n","X_train_unique.columns[sel.get_support()]"],"execution_count":23,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Int64Index([4356, 4363, 4366, 4368, 4372, 4373, 4374, 4375, 4376, 4380,\n","            ...\n","            5117, 5120, 5121, 5122, 5123, 5127, 5128, 5138, 5141, 5142],\n","           dtype='int64', length=257)"]},"metadata":{"tags":[]},"execution_count":23}]},{"cell_type":"code","metadata":{"id":"rKZsOU6dJtC-","executionInfo":{"status":"ok","timestamp":1602970608077,"user_tz":-330,"elapsed":10782,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"1b9aba09-34db-4db0-98c2-d52b836bc48c","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["len(X_train_unique.columns[sel.get_support()])"],"execution_count":24,"outputs":[{"output_type":"execute_result","data":{"text/plain":["257"]},"metadata":{"tags":[]},"execution_count":24}]},{"cell_type":"code","metadata":{"id":"koIBuZMYKDum","executionInfo":{"status":"ok","timestamp":1602970608078,"user_tz":-330,"elapsed":10570,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"0d9f703c-822b-44a0-ed12-a79a626acb2b","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["X_train_mi = sel.transform(X_train_unique)\n","X_test_mi = sel.transform(X_test_unique)\n","X_train_mi.shape"],"execution_count":25,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(57, 257)"]},"metadata":{"tags":[]},"execution_count":25}]},{"cell_type":"markdown","metadata":{"id":"6dOWPSsFkKaa"},"source":["### Selecting N/3 Features of f2"]},{"cell_type":"code","metadata":{"id":"DkKLz4vAK9la","executionInfo":{"status":"ok","timestamp":1602970608079,"user_tz":-330,"elapsed":10207,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"36e8042c-c606-4e4f-f6c4-032a0737e260","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["fc= f_classif(X_train, y_train) \n","len(fc[0])"],"execution_count":26,"outputs":[{"output_type":"execute_result","data":{"text/plain":["5147"]},"metadata":{"tags":[]},"execution_count":26}]},{"cell_type":"code","metadata":{"id":"hzi27xDELqqD","executionInfo":{"status":"ok","timestamp":1602970608079,"user_tz":-330,"elapsed":9817,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"d4190281-3a2c-4804-fa01-1bae4f56b7e1","colab":{"base_uri":"https://localhost:8080/","height":84}},"source":["fc[: 10]"],"execution_count":27,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(array([7.27230443, 2.54311235, 0.26106612, ..., 0.64247832, 5.08636676,\n","        0.21048496]),\n"," array([0.00927583, 0.11650721, 0.61143363, ..., 0.42626428, 0.02811434,\n","        0.6481955 ]))"]},"metadata":{"tags":[]},"execution_count":27}]},{"cell_type":"code","metadata":{"id":"W0BIq5RQcfnz","executionInfo":{"status":"ok","timestamp":1602970608080,"user_tz":-330,"elapsed":9650,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["#0.15 is multiplied to take 15% of total features\n","fvalue_selector = SelectKBest(f_classif, k =int(len(fc[0])/3*0.15) )"],"execution_count":28,"outputs":[]},{"cell_type":"code","metadata":{"id":"SRa57e0VlWVg","executionInfo":{"status":"ok","timestamp":1602970608081,"user_tz":-330,"elapsed":9341,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["features_kbest = fvalue_selector.fit_transform(X_train_unique, y_train)"],"execution_count":29,"outputs":[]},{"cell_type":"code","metadata":{"id":"ocZ7SzNsMdwY","executionInfo":{"status":"ok","timestamp":1602970608081,"user_tz":-330,"elapsed":9002,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"374982d2-ef91-4925-8d1c-268a23006bff","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["X_train_fc = fvalue_selector.transform(X_train_unique)\n","X_test_fc = fvalue_selector.transform(X_test_unique)\n","X_train_fc.shape"],"execution_count":30,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(57, 257)"]},"metadata":{"tags":[]},"execution_count":30}]},{"cell_type":"markdown","metadata":{"id":"HpE2sS-klGwi"},"source":["### Selecting N/3 Features of f3"]},{"cell_type":"code","metadata":{"id":"hevwIAKReWjO","executionInfo":{"status":"ok","timestamp":1602970608082,"user_tz":-330,"elapsed":8160,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"85ef7409-e2c9-4388-e790-9fc8e9d9282c","colab":{"base_uri":"https://localhost:8080/","height":84}},"source":["tt= t_test(X_train, y_train) \n","tt[: 10]"],"execution_count":31,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(array([2.89439079e+06, 9.73510051e+10, 4.30257673e+07, ...,\n","        4.14923672e+06, 1.28390453e+08, 4.52521949e+06]),\n"," array([1.57294534e-131, 5.13329967e-256, 9.16656362e-164, ...,\n","        7.86099172e-136, 8.03717832e-177, 7.23645335e-137]))"]},"metadata":{"tags":[]},"execution_count":31}]},{"cell_type":"code","metadata":{"id":"d6I6T7HZebru","executionInfo":{"status":"ok","timestamp":1602970608082,"user_tz":-330,"elapsed":7613,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["#0.15 is multiplied to take 15% of total features\n","tvalue_selector = SelectKBest(t_test, k =int(len(fc[0])/3*0.15) )"],"execution_count":32,"outputs":[]},{"cell_type":"code","metadata":{"id":"8n38V_4Sedg-","executionInfo":{"status":"ok","timestamp":1602970608593,"user_tz":-330,"elapsed":7528,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["featurestt_kbest = tvalue_selector.fit_transform(X_train_unique, y_train)"],"execution_count":33,"outputs":[]},{"cell_type":"code","metadata":{"id":"Fsyx1sMYefXi","executionInfo":{"status":"ok","timestamp":1602970608593,"user_tz":-330,"elapsed":6855,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"252c99b9-4061-4d8d-d2eb-553aed9a6c31","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["X_train_t = tvalue_selector.transform(X_train_unique)\n","X_test_t = tvalue_selector.transform(X_test_unique)\n","X_train_t.shape"],"execution_count":34,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(57, 257)"]},"metadata":{"tags":[]},"execution_count":34}]},{"cell_type":"markdown","metadata":{"id":"ipkXrknSlI_h"},"source":["### Task B.1: Taking Union of f1, f2, f3"]},{"cell_type":"code","metadata":{"id":"XYhKHU2-lQCU","executionInfo":{"status":"ok","timestamp":1602970619392,"user_tz":-330,"elapsed":15659,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["from sklearn.pipeline import FeatureUnion, Pipeline\n","combined_features = FeatureUnion([(\"mi\", sel), (\"fc\",fvalue_selector ),(\"tt\",tvalue_selector)])\n","\n","# Use combined features to transform dataset:\n","X_train_uni = combined_features.fit(X_train_unique, y_train).transform(X_train_unique)\n","X_test_uni = combined_features.fit(X_train_unique, y_train).transform(X_test_unique)"],"execution_count":35,"outputs":[]},{"cell_type":"code","metadata":{"id":"TpRyG6FJn40Z","executionInfo":{"status":"ok","timestamp":1602970619394,"user_tz":-330,"elapsed":14946,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"24f2809c-9172-4fb8-ba40-a8d2b11a61e5","colab":{"base_uri":"https://localhost:8080/","height":33}},"source":["X_train_uni.shape"],"execution_count":36,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(57, 771)"]},"metadata":{"tags":[]},"execution_count":36}]},{"cell_type":"markdown","metadata":{"id":"LK4i-I6NX8KE"},"source":["## Task B.2: Application Of KNN (C1)"]},{"cell_type":"code","metadata":{"id":"b-9KCWt_Mypy","executionInfo":{"status":"ok","timestamp":1602970619395,"user_tz":-330,"elapsed":13533,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"5aacb69d-fec2-4124-9686-d336337b8474","colab":{"base_uri":"https://localhost:8080/","height":318}},"source":["%%time\n","run_knn(X_train_uni, X_test_uni, y_train, y_test)"],"execution_count":37,"outputs":[{"output_type":"stream","text":["Training 80% data report::\n","Accuracy Score: \n","0.9473684210526315\n","F1-Score: \n","0.9599999999999999\n","Confusion Matrix: \n","[[18  2]\n"," [ 1 36]]\n","Testing 20% data report::\n","Accuracy Score: \n","0.9333333333333333\n","F1-Score: \n","0.9523809523809523\n","Confusion Matrix: \n","[[ 4  1]\n"," [ 0 10]]\n","CPU times: user 37.2 ms, sys: 1.99 ms, total: 39.2 ms\n","Wall time: 38.8 ms\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"EYJLOvw7X__H"},"source":["## Task B.3: Application Of SVM (C2)"]},{"cell_type":"code","metadata":{"id":"jCN5_yH5KcFM","executionInfo":{"status":"ok","timestamp":1602970619398,"user_tz":-330,"elapsed":12244,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"1e1dccb8-f50d-4d75-84a9-99f8d352de5d","colab":{"base_uri":"https://localhost:8080/","height":318}},"source":["%%time\n","run_svm(X_train_uni, X_test_uni, y_train, y_test)"],"execution_count":38,"outputs":[{"output_type":"stream","text":["Training 80% data report::\n","Accuracy Score: \n","0.9473684210526315\n","F1-Score: \n","0.961038961038961\n","Confusion Matrix: \n","[[17  3]\n"," [ 0 37]]\n","Testing 20% data report::\n","Accuracy Score: \n","0.9333333333333333\n","F1-Score: \n","0.9523809523809523\n","Confusion Matrix: \n","[[ 4  1]\n"," [ 0 10]]\n","CPU times: user 38.7 ms, sys: 1.05 ms, total: 39.8 ms\n","Wall time: 38.5 ms\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"CH5hKbkspNLT"},"source":["## Task B.4: Comparison is done in separate file comparison.docx"]},{"cell_type":"markdown","metadata":{"id":"_DdvdcllpDnq"},"source":["### End of Task B"]}]}