def predict_proba(self, X):
        """Predict class probabilities using the fitted underlying estimator
        and the reduced dataset.

        Parameters
        ----------
        X : pandas.DataFrame (n_samples, n_features)
            Training vector, where n_samples is the number of samples.

        Returns
        -------
        p: array of shape (n_samples, n_classes)
            The class probabilities of the input samples.
        """
        X_t = self._transform(
            X=X, metric=None, metric_special=self._metric_special,
            metric_missing=self._metric_missing)

        return self.estimator_.predict_proba(X_t)
Predict class probabilities using the fitted underlying estimator
        and the reduced dataset.

        Parameters
        ----------
        X : pandas.DataFrame (n_samples, n_features)
            Training vector, where n_samples is the number of samples.

        Returns
        -------
        p: array of shape (n_samples, n_classes)
            The class probabilities of the input samples.
        
optbinning/scorecard/scorecard.py