docs: def score(self, X, y=None, train=False, **kwargs):
          """
          Generates predicted target values using the Scikit-Learn
          estimator.
  
          Parameters
          ----------
          X : array-like
              X (also X_test) are the dependent variables of test set to predict
  
          y : array-like
              y (also y_test) is the independent actual variables to score against
  
          train : boolean
              If False, `score` assumes that the residual points being plotted
              are from the test data; if True, `score` assumes the residuals
              are the train data.
  
          Returns
          ------
          score : float
              The score of the underlying estimator, usually the R-squared score
              for regression estimators.
          """
          score = self.estimator.score(X, y, **kwargs)
          if train:
              self.train_score_ = score
          else:
              self.test_score_ = score
  
          y_pred = self.predict(X)
          scores = y_pred - y
          self.draw(y_pred, scores, train=train)
          
          return score