title: How to remove all non zero important features using feature_importances_ in Decision Tree?
body: <p>I'm trying to build a new dataset for analysis where I need to remove all the non-zero important features from the original dataset.</p>
  
  <p>My dataset shape is (61176, 13047) after preproceesing.</p>
  
  <p>I have found the features importance of all the features as below:</p>
  
  <pre><code>clf_features = DecisionTreeClassifier(min_samples_split=2,class_weight = 'balanced')
  clf_features.fit(x_trn_tfidf, y_train)
  </code></pre>
  
  <p>I got the feature importance for all the features in numpy array.</p>
  
  <p>Now I need to remove all the non-zero important features (i.e for eg values less than 0.001) and create a new dataset.</p>
  
  <p>Can someone suggest how to do this?</p>