code: def predict_proba(self, X):
      if self.estimator is None:
          raise NotImplementedError()
      return self.estimator.predict_proba(X)
  
file_path: auto-sklearn/examples/80_extending/example_extending_classification.py
imports: from typing import Optional
  from pprint import pprint
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, UniformIntegerHyperparameter, UniformFloatHyperparameter
  import sklearn.metrics
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  import autosklearn.classification
  import autosklearn.pipeline.components.classification
  from autosklearn.pipeline.components.base import AutoSklearnClassificationAlgorithm
  from autosklearn.pipeline.constants import DENSE, SIGNED_DATA, UNSIGNED_DATA, PREDICTIONS
  from sklearn.datasets import load_breast_cancer
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 4 for calling the MLPClassifier obj's underlying member method code with example usage: obj.predict_proba(X) and returns: self