code: def compute_metrics_cv(self, X, y, **kwargs):
          '''Compute cross-validated metrics.
  
          Trains this model on data X with labels y.
          Returns a list of dict with keys name, scoring_name, value.
  
          Args:
          X (Union[np.array, pd.DataFrame]): data
          y (Union[np.array, pd.DataFrame, pd.Series]): labels
          '''
  
          # compute scores
          results = self.cv_score_mean(X, y)
          return resultf compute_metrics_cv(self, X, y, **kwargs):
          '''Compute cross-validated metrics.
  
          Trains this model on data X with labels y.
          Returns a list of dict with keys name, scoring_name, value.
  
          Args:
          X (Union[np.array, pd.DataFrame]): data
          y (Union[np.array, pd.DataFrame, pd.Series]): labels
          '''
  
          # compute scores
          results = self.cv_score_mean(X, y)
          return results
docs: Compute cross-validated metrics.
  
          Trains this model on data X with labels y.
          Returns a list of dict with keys name, scoring_name, value.
  
          Args:
          X (Union[np.array, pd.DataFrame]): data
          y (Union[np.array, pd.DataFrame, pd.Series]): labels