code: def predict(self, X):
      if self.estimator is None:
          raise NotImplementedError
      return self.estimator.predict(X)
  
file_path: auto-sklearn/examples/80_extending/example_extending_regression.py
imports: from typing import Optional
  from pprint import pprint
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import UniformFloatHyperparameter, UniformIntegerHyperparameter, CategoricalHyperparameter
  from ConfigSpace.conditions import EqualsCondition
  import sklearn.metrics
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  import autosklearn.regression
  import autosklearn.pipeline.components.regression
  from autosklearn.pipeline.components.base import AutoSklearnRegressionAlgorithm
  from autosklearn.pipeline.constants import SPARSE, DENSE, SIGNED_DATA, UNSIGNED_DATA, PREDICTIONS
  from sklearn.datasets import load_diabetes
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 3 for calling the KernelRidgeRegression obj's underlying member method code with example usage: obj.predict(X) and returns: self