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.

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