Apply transforms, and predict_log_proba of the final estimator

        Parameters
        ----------
        X : iterable
            Data to predict on. Must fulfill input requirements of first step
            of the pipeline.

        Returns
        -------
        y_score : array-like, shape = [n_samples, n_classes]

def predict_log_proba(self, X):
        """
        Apply transforms, and predict_log_proba of the final estimator

        Parameters
        ----------
        X : iterable
            Data to predict on. Must fulfill input requirements of first step
            of the pipeline.

        Returns
        -------
        y_score : array-like, shape = [n_samples, n_classes]
        """
        Xt, _, _ = self._transform(X)
        return self._final_estimator.predict_log_proba(Xt)