rf = RandomForestClassifier(n_jobs=-1, class_weight='balanced', max_depth=5)
feat_selector = BorutaPy(rf, n_estimators='auto', verbose=3, random_state=1)
feat_selector.fit(X_std, y)
feat_selector.support_