docs: def get_diversity(self,X):
          """compute mean diversity of individual outputs"""
          # diversity in terms of cosine distances between features
          feature_correlations = np.zeros(X.shape[0]-1)
          for i in np.arange(1,X.shape[0]-1):
              feature_correlations[i] = max(0.0,r2_score(X[0],X[i]))
          # pdb.set_trace()
          self.diversity.append(1-np.mean(feature_correlations))