title: How to run Machine Learning algorithms in GPU
body: <p>I have used backward elimination algorithm to reduce features. But the point is with large amount of features and samples, it run on CPU and pretty slow.</p>
  <p>How could i run it multithreading on GPU like i train Deep Learning. This is my code</p>
  <pre><code>import pandas as pd
  data = pd.read_csv('data.csv')
  X = data.drop(['Path','id','label'], axis=1)
  y = data['label']
  
  from mlxtend.feature_selection import SequentialFeatureSelector as sfs
  from sklearn.linear_model import LinearRegression
  lreg = LinearRegression()
  new_sfs = sfs(lreg, k_features=1600, forward=False, verbose=1, scoring='neg_mean_squared_error')
  new_sfs = new_sfs.fit(X, y)
  feat_names = list(sfs1.k_feature_names_)
  </code></pre>