code: def decision_function(self, X):
          
          Xt, _, _ = self._transform(X)
          return self._final_estimator.decision_function(Xt)
docs: Apply transforms, and decision_function 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]