code: def predict_features(self, df_features, df_target, idx=0, **kwargs):
          
          X = df_features.values
          y = df_target.values
          regressor = DecisionTreeRegressor()
          regressor.fit(X, y)
  
          return regressor.feature_importances_
docs: For one variable, predict its neighbouring nodes.
  
          Args:
              df_features (pandas.DataFrame):
              df_target (pandas.Series):
              idx (int): (optional) for printing purposes
              kwargs (dict): additional options for algorithms
  
          Returns:
              list: scores of each feature relatively to the target