code: def predict(self, X, raw_score=False, num_iteration=None,
                  pred_leaf=False, pred_contrib=False, **kwargs):
          
          result = self.predict_proba(X, raw_score, num_iteration,
                                      pred_leaf, pred_contrib, **kwargs)
          if raw_score or pred_leaf or pred_contrib:
              return result
          else:
              class_index = np.argmax(result, axis=1)
              return self._le.inverse_transform(class_index)
docs: Docstring is inherited from the LGBMModel.