create_rfe_feature_selection.py

def create_rfe_feature_selection(df, target_feature, n_features=3):
  columns_list = list(df.columns)
  columns_list.remove(target_feature)

  logreg = LogisticRegression(solver='lbfgs')
  rfe = RFE(logreg, n_features)
  rfe = rfe.fit(df[columns_list],df[target_feature].values.ravel())
  filtered_rfe_list = list(compress(df.columns, rfe.support_))
  print(rfe.support_)
  print(rfe.ranking_)
  print(filtered_rfe_list)
  return [x for _,x in sorted(zip(rfe.ranking_,columns_list))]