Leukemia Feature Selection Task D.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Leukemia Feature Selection Task D.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true,"authorship_tag":"ABX9TyPzUmuK+SAXTaXaT5u8MRrp"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"id":"XRW276KYgn1z","executionInfo":{"status":"ok","timestamp":1602872868105,"user_tz":-330,"elapsed":8779,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"f195dec9-860e-46bb-c6a2-e03f29287c65","colab":{"base_uri":"https://localhost:8080/","height":255}},"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 3.2MB/s \n","\u001b[?25hRequirement already satisfied, skipping upgrade: numpy>=1.13.3 in /usr/local/lib/python3.6/dist-packages (from scikit-learn) (1.18.5)\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","Collecting threadpoolctl>=2.0.0\n","  Downloading https://files.pythonhosted.org/packages/f7/12/ec3f2e203afa394a149911729357aa48affc59c20e2c1c8297a60f33f133/threadpoolctl-2.1.0-py3-none-any.whl\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":"l-MNYqlDhZmZ","executionInfo":{"status":"ok","timestamp":1602872871046,"user_tz":-330,"elapsed":11628,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"4fb8cc28-5c07-4a18-d143-e22c59edfc3c","colab":{"base_uri":"https://localhost:8080/","height":406}},"source":["!pip install -U mlxtend"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Collecting mlxtend\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/4c/0d/4a73b8bc49e2cfee178fe50dd8e84d5ba817d0b2454b09308397416e0e48/mlxtend-0.17.3-py2.py3-none-any.whl (1.3MB)\n","\u001b[K     |████████████████████████████████| 1.3MB 3.4MB/s \n","\u001b[?25hRequirement already satisfied, skipping upgrade: matplotlib>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from mlxtend) (3.2.2)\n","Requirement already satisfied, skipping upgrade: scipy>=1.2.1 in /usr/local/lib/python3.6/dist-packages (from mlxtend) (1.4.1)\n","Requirement already satisfied, skipping upgrade: setuptools in /usr/local/lib/python3.6/dist-packages (from mlxtend) (50.3.0)\n","Requirement already satisfied, skipping upgrade: numpy>=1.16.2 in /usr/local/lib/python3.6/dist-packages (from mlxtend) (1.18.5)\n","Requirement already satisfied, skipping upgrade: scikit-learn>=0.20.3 in /usr/local/lib/python3.6/dist-packages (from mlxtend) (0.23.2)\n","Requirement already satisfied, skipping upgrade: pandas>=0.24.2 in /usr/local/lib/python3.6/dist-packages (from mlxtend) (1.1.2)\n","Requirement already satisfied, skipping upgrade: joblib>=0.13.2 in /usr/local/lib/python3.6/dist-packages (from mlxtend) (0.16.0)\n","Requirement already satisfied, skipping upgrade: python-dateutil>=2.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.0.0->mlxtend) (2.8.1)\n","Requirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.0.0->mlxtend) (1.2.0)\n","Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.0.0->mlxtend) (0.10.0)\n","Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.0.0->mlxtend) (2.4.7)\n","Requirement already satisfied, skipping upgrade: threadpoolctl>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from scikit-learn>=0.20.3->mlxtend) (2.1.0)\n","Requirement already satisfied, skipping upgrade: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.24.2->mlxtend) (2018.9)\n","Requirement already satisfied, skipping upgrade: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.1->matplotlib>=3.0.0->mlxtend) (1.15.0)\n","Installing collected packages: mlxtend\n","  Found existing installation: mlxtend 0.14.0\n","    Uninstalling mlxtend-0.14.0:\n","      Successfully uninstalled mlxtend-0.14.0\n","Successfully installed mlxtend-0.17.3\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"0V2ggHzhMII-","executionInfo":{"status":"ok","timestamp":1602872871835,"user_tz":-330,"elapsed":11702,"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":3,"outputs":[]},{"cell_type":"code","metadata":{"id":"IhmnO4Y4M3_q","executionInfo":{"status":"ok","timestamp":1602872909634,"user_tz":-330,"elapsed":1382,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"d874455b-0282-461f-e2a0-24eff17d5ec0","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["#importing dataset\n","df = pd.read_csv('leukemia.tab', delimiter='\\t')\n","df.shape"],"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(75, 5148)"]},"metadata":{"tags":[]},"execution_count":4}]},{"cell_type":"code","metadata":{"id":"sh50eO6FNUvG","executionInfo":{"status":"ok","timestamp":1602872910960,"user_tz":-330,"elapsed":1059,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"6e541c59-e481-4d19-fd2a-127e3d29a0af","colab":{"base_uri":"https://localhost:8080/","height":278}},"source":["df.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>gene</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>...</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>0</th>\n","      <td>discrete</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>...</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","      <td>continuous</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>class</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>ALL</td>\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>...</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","      <td>349</td>\n","      <td>61</td>\n","      <td>273</td>\n","      <td>384</td>\n","      <td>1582</td>\n","      <td>185</td>\n","      <td>511</td>\n","      <td>389</td>\n","      <td>793</td>\n","      <td>329</td>\n","      <td>36</td>\n","      <td>191</td>\n","      <td>-37</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>ALL</td>\n","      <td>283</td>\n","      <td>11038</td>\n","      <td>134</td>\n","      <td>-21</td>\n","      <td>-219</td>\n","      <td>116</td>\n","      <td>433</td>\n","      <td>615</td>\n","      <td>115</td>\n","      <td>1518</td>\n","      <td>19448</td>\n","      <td>13568</td>\n","      <td>18112</td>\n","      <td>17926</td>\n","      <td>20668</td>\n","      <td>16959</td>\n","      <td>513</td>\n","      <td>153</td>\n","      <td>285</td>\n","      <td>2215</td>\n","      <td>3824</td>\n","      <td>3187</td>\n","      <td>301</td>\n","      <td>530</td>\n","      <td>418</td>\n","      <td>263</td>\n","      <td>21</td>\n","      <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>...</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","      <td>143</td>\n","      <td>231</td>\n","      <td>624</td>\n","      <td>169</td>\n","      <td>837</td>\n","      <td>442</td>\n","      <td>782</td>\n","      <td>295</td>\n","      <td>11</td>\n","      <td>76</td>\n","      <td>-14</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>ALL</td>\n","      <td>309</td>\n","      <td>16692</td>\n","      <td>378</td>\n","      <td>67</td>\n","      <td>104</td>\n","      <td>476</td>\n","      <td>1474</td>\n","      <td>5669</td>\n","      <td>3272</td>\n","      <td>3668</td>\n","      <td>27410</td>\n","      <td>16756</td>\n","      <td>23006</td>\n","      <td>22626</td>\n","      <td>24672</td>\n","      <td>18285</td>\n","      <td>609</td>\n","      <td>66</td>\n","      <td>187</td>\n","      <td>3325</td>\n","      <td>3349</td>\n","      <td>3097</td>\n","      <td>524</td>\n","      <td>911</td>\n","      <td>761</td>\n","      <td>88</td>\n","      <td>-27</td>\n","      <td>358</td>\n","      <td>42</td>\n","      <td>142</td>\n","      <td>359</td>\n","      <td>237</td>\n","      <td>1997</td>\n","      <td>91</td>\n","      <td>2514</td>\n","      <td>-603</td>\n","      <td>362</td>\n","      <td>-31</td>\n","      <td>270</td>\n","      <td>...</td>\n","      <td>383</td>\n","      <td>36</td>\n","      <td>157</td>\n","      <td>28</td>\n","      <td>12</td>\n","      <td>-213</td>\n","      <td>426</td>\n","      <td>687</td>\n","      <td>387</td>\n","      <td>-474</td>\n","      <td>180</td>\n","      <td>272</td>\n","      <td>591</td>\n","      <td>959</td>\n","      <td>24292</td>\n","      <td>17378</td>\n","      <td>1808</td>\n","      <td>363</td>\n","      <td>325</td>\n","      <td>6560</td>\n","      <td>5023</td>\n","      <td>1090</td>\n","      <td>9</td>\n","      <td>220</td>\n","      <td>-58</td>\n","      <td>294</td>\n","      <td>143</td>\n","      <td>464</td>\n","      <td>513</td>\n","      <td>238</td>\n","      <td>720</td>\n","      <td>753</td>\n","      <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","  </tbody>\n","</table>\n","<p>5 rows × 5148 columns</p>\n","</div>"],"text/plain":["       gene AFFX-BioC-5_at  hum_alu_at  ... L49218_f_at M71243_f_at Z78285_f_at\n","0  discrete     continuous  continuous  ...  continuous  continuous  continuous\n","1     class            NaN         NaN  ...         NaN         NaN         NaN\n","2       ALL             88       15091  ...          36         191         -37\n","3       ALL            283       11038  ...          11          76         -14\n","4       ALL            309       16692  ...          41         228         -41\n","\n","[5 rows x 5148 columns]"]},"metadata":{"tags":[]},"execution_count":5}]},{"cell_type":"code","metadata":{"id":"XwbZnDMKNZWX","executionInfo":{"status":"ok","timestamp":1602872925118,"user_tz":-330,"elapsed":927,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}}},"source":["df=df.dropna().loc[1:,:]"],"execution_count":6,"outputs":[]},{"cell_type":"code","metadata":{"id":"62_oXKSlNuek","executionInfo":{"status":"ok","timestamp":1602872939667,"user_tz":-330,"elapsed":923,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"825b8a02-2048-457c-dd84-79870fcfdc60","colab":{"base_uri":"https://localhost:8080/","height":278}},"source":["X = df.drop(['gene'], axis=1)\n","X.head()"],"execution_count":7,"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","      <td>349</td>\n","      <td>61</td>\n","      <td>273</td>\n","      <td>384</td>\n","      <td>1582</td>\n","      <td>185</td>\n","      <td>511</td>\n","      <td>389</td>\n","      <td>793</td>\n","      <td>329</td>\n","      <td>36</td>\n","      <td>191</td>\n","      <td>-37</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>283</td>\n","      <td>11038</td>\n","      <td>134</td>\n","      <td>-21</td>\n","      <td>-219</td>\n","      <td>116</td>\n","      <td>433</td>\n","      <td>615</td>\n","      <td>115</td>\n","      <td>1518</td>\n","      <td>19448</td>\n","      <td>13568</td>\n","      <td>18112</td>\n","      <td>17926</td>\n","      <td>20668</td>\n","      <td>16959</td>\n","      <td>513</td>\n","      <td>153</td>\n","      <td>285</td>\n","      <td>2215</td>\n","      <td>3824</td>\n","      <td>3187</td>\n","      <td>301</td>\n","      <td>530</td>\n","      <td>418</td>\n","      <td>263</td>\n","      <td>21</td>\n","      <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","      <td>143</td>\n","      <td>231</td>\n","      <td>624</td>\n","      <td>169</td>\n","      <td>837</td>\n","      <td>442</td>\n","      <td>782</td>\n","      <td>295</td>\n","      <td>11</td>\n","      <td>76</td>\n","      <td>-14</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>309</td>\n","      <td>16692</td>\n","      <td>378</td>\n","      <td>67</td>\n","      <td>104</td>\n","      <td>476</td>\n","      <td>1474</td>\n","      <td>5669</td>\n","      <td>3272</td>\n","      <td>3668</td>\n","      <td>27410</td>\n","      <td>16756</td>\n","      <td>23006</td>\n","      <td>22626</td>\n","      <td>24672</td>\n","      <td>18285</td>\n","      <td>609</td>\n","      <td>66</td>\n","      <td>187</td>\n","      <td>3325</td>\n","      <td>3349</td>\n","      <td>3097</td>\n","      <td>524</td>\n","      <td>911</td>\n","      <td>761</td>\n","      <td>88</td>\n","      <td>-27</td>\n","      <td>358</td>\n","      <td>42</td>\n","      <td>142</td>\n","      <td>359</td>\n","      <td>237</td>\n","      <td>1997</td>\n","      <td>91</td>\n","      <td>2514</td>\n","      <td>-603</td>\n","      <td>362</td>\n","      <td>-31</td>\n","      <td>270</td>\n","      <td>603</td>\n","      <td>...</td>\n","      <td>383</td>\n","      <td>36</td>\n","      <td>157</td>\n","      <td>28</td>\n","      <td>12</td>\n","      <td>-213</td>\n","      <td>426</td>\n","      <td>687</td>\n","      <td>387</td>\n","      <td>-474</td>\n","      <td>180</td>\n","      <td>272</td>\n","      <td>591</td>\n","      <td>959</td>\n","      <td>24292</td>\n","      <td>17378</td>\n","      <td>1808</td>\n","      <td>363</td>\n","      <td>325</td>\n","      <td>6560</td>\n","      <td>5023</td>\n","      <td>1090</td>\n","      <td>9</td>\n","      <td>220</td>\n","      <td>-58</td>\n","      <td>294</td>\n","      <td>143</td>\n","      <td>464</td>\n","      <td>513</td>\n","      <td>238</td>\n","      <td>720</td>\n","      <td>753</td>\n","      <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","      <td>2128</td>\n","      <td>-82</td>\n","      <td>1489</td>\n","      <td>-909</td>\n","      <td>266</td>\n","      <td>-181</td>\n","      <td>115</td>\n","      <td>255</td>\n","      <td>...</td>\n","      <td>223</td>\n","      <td>-46</td>\n","      <td>90</td>\n","      <td>-19</td>\n","      <td>-36</td>\n","      <td>-87</td>\n","      <td>534</td>\n","      <td>376</td>\n","      <td>317</td>\n","      <td>-336</td>\n","      <td>325</td>\n","      <td>149</td>\n","      <td>173</td>\n","      <td>431</td>\n","      <td>17558</td>\n","      <td>13818</td>\n","      <td>576</td>\n","      <td>455</td>\n","      <td>594</td>\n","      <td>8955</td>\n","      <td>9567</td>\n","      <td>1708</td>\n","      <td>45</td>\n","      <td>430</td>\n","      <td>-35</td>\n","      <td>128</td>\n","      <td>22</td>\n","      <td>342</td>\n","      <td>142</td>\n","      <td>277</td>\n","      <td>307</td>\n","      <td>743</td>\n","      <td>240</td>\n","      <td>835</td>\n","      <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":7}]},{"cell_type":"code","metadata":{"id":"3RyMVKS9OdXH","executionInfo":{"status":"ok","timestamp":1602872966380,"user_tz":-330,"elapsed":921,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"cf22b3a3-2cfe-4390-c056-9e5d13c8ada5","colab":{"base_uri":"https://localhost:8080/","height":118}},"source":["# Mapping genes into integers\n","y = df['gene']\n","y=y.map({'ALL': 1, 'AML': 0})\n","y.head()"],"execution_count":8,"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":8}]},{"cell_type":"code","metadata":{"id":"astqC66ha-yq","executionInfo":{"status":"ok","timestamp":1602872969337,"user_tz":-330,"elapsed":1055,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"065fc19a-5835-4ce7-fa08-b9fe930cb169","colab":{"base_uri":"https://localhost:8080/","height":218}},"source":["df.dtypes"],"execution_count":9,"outputs":[{"output_type":"execute_result","data":{"text/plain":["gene              object\n","AFFX-BioC-5_at    object\n","hum_alu_at        object\n","AFFX-DapX-M_at    object\n","AFFX-LysX-5_at    object\n","                   ...  \n","X83863_at         object\n","Z17240_at         object\n","L49218_f_at       object\n","M71243_f_at       object\n","Z78285_f_at       object\n","Length: 5148, dtype: object"]},"metadata":{"tags":[]},"execution_count":9}]},{"cell_type":"code","metadata":{"id":"nYy7FrcDTzwB","executionInfo":{"status":"ok","timestamp":1602872970791,"user_tz":-330,"elapsed":1079,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"d73538ad-c47f-42f3-8230-35b7f00ffe2f","colab":{"base_uri":"https://localhost:8080/","height":50}},"source":["print(X.shape)\n","print(y.shape)"],"execution_count":10,"outputs":[{"output_type":"stream","text":["(72, 5147)\n","(72,)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"RnLB1lnpOiCl","executionInfo":{"status":"ok","timestamp":1602872974768,"user_tz":-330,"elapsed":1196,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"5b331dab-66ad-4a23-be4c-de570c476799","colab":{"base_uri":"https://localhost:8080/","height":34}},"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":11,"outputs":[{"output_type":"execute_result","data":{"text/plain":["((57, 5147), (57,), (15, 5147), (15,))"]},"metadata":{"tags":[]},"execution_count":11}]},{"cell_type":"markdown","metadata":{"id":"KlQ6AMXIoSHc"},"source":["Due to huge amount of time taken to train these models, I am assigning N=k_features=3."]},{"cell_type":"markdown","metadata":{"id":"pIEvto9Cn39w"},"source":["## Task D.1: Classifying Data with Wrapper Model Sequential Forward Search"]},{"cell_type":"code","metadata":{"id":"4jCbeObxgpw_","executionInfo":{"status":"ok","timestamp":1602873026364,"user_tz":-330,"elapsed":47765,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"c70e7633-9b0e-49f3-b814-f8dd55c8f4c5","colab":{"base_uri":"https://localhost:8080/","height":235}},"source":["from sklearn.neighbors import KNeighborsClassifier\n","from mlxtend.feature_selection import SequentialFeatureSelector as SFS\n","knn = KNeighborsClassifier(n_neighbors=3)\n","sfs1 = SFS(knn, \n","           k_features=3, \n","           forward=True, \n","           floating=False, \n","           verbose=2,\n","           scoring='accuracy',\n","           cv=0)\n","\n","sfs1 = sfs1.fit(X_train, y_train)"],"execution_count":12,"outputs":[{"output_type":"stream","text":["[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n","[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n","[Parallel(n_jobs=1)]: Done 5147 out of 5147 | elapsed:   15.5s finished\n","\n","[2020-10-16 18:29:54] Features: 1/3 -- score: 0.9824561403508771[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n","[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n","[Parallel(n_jobs=1)]: Done 5146 out of 5146 | elapsed:   15.5s finished\n","\n","[2020-10-16 18:30:10] Features: 2/3 -- score: 1.0[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n","[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n","[Parallel(n_jobs=1)]: Done 5145 out of 5145 | elapsed:   15.1s finished\n","\n","[2020-10-16 18:30:25] Features: 3/3 -- score: 1.0"],"name":"stderr"}]},{"cell_type":"code","metadata":{"id":"liXkLqV1jxLl","executionInfo":{"status":"ok","timestamp":1602873026366,"user_tz":-330,"elapsed":44420,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"89683770-7779-4947-b1d6-b4fbb4e1ad9c","colab":{"base_uri":"https://localhost:8080/","height":136}},"source":["pd.DataFrame.from_dict(sfs1.get_metric_dict()).T"],"execution_count":13,"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>feature_idx</th>\n","      <th>cv_scores</th>\n","      <th>avg_score</th>\n","      <th>feature_names</th>\n","      <th>ci_bound</th>\n","      <th>std_dev</th>\n","      <th>std_err</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>1</th>\n","      <td>(1335,)</td>\n","      <td>[0.9824561403508771]</td>\n","      <td>0.982456</td>\n","      <td>(M23197_at,)</td>\n","      <td>NaN</td>\n","      <td>0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>(107, 1335)</td>\n","      <td>[1.0]</td>\n","      <td>1</td>\n","      <td>(D10495_at, M23197_at)</td>\n","      <td>NaN</td>\n","      <td>0</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>(3, 107, 1335)</td>\n","      <td>[1.0]</td>\n","      <td>1</td>\n","      <td>(AFFX-LysX-5_at, D10495_at, M23197_at)</td>\n","      <td>NaN</td>\n","      <td>0</td>\n","      <td>NaN</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["      feature_idx             cv_scores avg_score  ... ci_bound std_dev std_err\n","1         (1335,)  [0.9824561403508771]  0.982456  ...      NaN       0     NaN\n","2     (107, 1335)                 [1.0]         1  ...      NaN       0     NaN\n","3  (3, 107, 1335)                 [1.0]         1  ...      NaN       0     NaN\n","\n","[3 rows x 7 columns]"]},"metadata":{"tags":[]},"execution_count":13}]},{"cell_type":"code","metadata":{"id":"SLgGSc2UjbYx","executionInfo":{"status":"ok","timestamp":1602873026368,"user_tz":-330,"elapsed":43727,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"02bf7026-0bb8-4cdf-fef7-fd76cfa5e137","colab":{"base_uri":"https://localhost:8080/","height":295}},"source":["from mlxtend.plotting import plot_sequential_feature_selection as plot_sfs\n","fig1 = plot_sfs(sfs1.get_metric_dict(), kind='std_dev')\n","\n","plt.ylim([0.8, 1])\n","plt.title('Sequential Forward Selection (w. StdDev)')\n","plt.grid()\n","plt.show()"],"execution_count":14,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"4RxpYyB_oKKH"},"source":["## Task D.2: Classifying Data with Wrapper Model Sequential Backward Search"]},{"cell_type":"code","metadata":{"id":"nUkbjafhkQQi","executionInfo":{"status":"ok","timestamp":1602873134290,"user_tz":-330,"elapsed":150109,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"7b03c95e-323b-4a26-f1f3-f21de7377374","colab":{"base_uri":"https://localhost:8080/","height":84}},"source":["knn = KNeighborsClassifier(n_neighbors=3)\n","sbs1 = SFS(knn, \n","           k_features=1060, \n","           forward=False,#False for backward approach \n","           floating=False, \n","           verbose=2,\n","           scoring='accuracy',\n","           cv=0)\n","\n","sbs1 = sbs1.fit(X_train, y_train)"],"execution_count":15,"outputs":[{"output_type":"stream","text":["[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.\n","[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.1s remaining:    0.0s\n","\n","STOPPING EARLY DUE TO KEYBOARD INTERRUPT..."],"name":"stderr"}]},{"cell_type":"markdown","metadata":{"id":"8jz28HbOqOdM"},"source":["### Due to huge time taken, I have given Keyboard Interrupt to stop the job."]},{"cell_type":"code","metadata":{"id":"MWpdNI4IkjqL","executionInfo":{"status":"ok","timestamp":1602873134293,"user_tz":-330,"elapsed":146836,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"ee5a1ffd-befe-4023-f40a-1a776e9160d4","colab":{"base_uri":"https://localhost:8080/","height":94}},"source":["pd.DataFrame.from_dict(sbs1.get_metric_dict()).T"],"execution_count":16,"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>avg_score</th>\n","      <th>ci_bound</th>\n","      <th>cv_scores</th>\n","      <th>feature_idx</th>\n","      <th>feature_names</th>\n","      <th>std_dev</th>\n","      <th>std_err</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>5147</th>\n","      <td>0.964912</td>\n","      <td>NaN</td>\n","      <td>[0.9649122807017544]</td>\n","      <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n","      <td>(AFFX-BioC-5_at, hum_alu_at, AFFX-DapX-M_at, A...</td>\n","      <td>0</td>\n","      <td>NaN</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["     avg_score ci_bound  ... std_dev std_err\n","5147  0.964912      NaN  ...       0     NaN\n","\n","[1 rows x 7 columns]"]},"metadata":{"tags":[]},"execution_count":16}]},{"cell_type":"code","metadata":{"id":"Iiu9PWoxk3aH","executionInfo":{"status":"ok","timestamp":1602873134295,"user_tz":-330,"elapsed":145870,"user":{"displayName":"SAURABH SHARMA","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GiEQtz7tp9CtnjpNjSaFTHronhHsCfUBJCX_QFjRw=s64","userId":"12707603287526165163"}},"outputId":"b78ff2c6-3999-464f-e95d-6faf309529ca","colab":{"base_uri":"https://localhost:8080/","height":295}},"source":["fig1 = plot_sfs(sbs1.get_metric_dict(), kind='std_dev')\n","\n","plt.ylim([0.8, 1])\n","plt.title('Sequential Backward Selection (w. StdDev)')\n","plt.grid()\n","plt.show()"],"execution_count":17,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"ZL4OX3mMo3id"},"source":["### End of All Tasks and Assignment"]}]}