code: def score_uncertainty(self, X):
      Xt = X
      for name, transform in self.steps[:-1]:
          if transform is not None:
              Xt = transform.transform(Xt)
      return self.steps[-1][-1].score_uncertainty(Xt)
  
imports: import csv
  import datetime
  import numbers
  import os
  import pkg_resources
  import numpy
  import pandas
  import scipy
  from sklearn.datasets import load_boston
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import LabelEncoder
  from sklearn.utils.metaestimators import if_delegate_has_method
  from sklearn.utils import column_or_1d
  from auto_ml._version import __version__
label_desc: Use image node_id 3 for calling the ExtendedPipeline obj's underlying member method code with example usage: obj.score_uncertainty(X) and returns: self