class_docstr: Provide an abstract interface for preprocessing algorithms in
  auto-sklearn.
  
  See :ref:`extending` for more information.
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docstr: The transform function calls the transform function of the
  underlying scikit-learn model and returns the transformed array.
  
  Parameters
  ----------
  X : array-like, shape = (n_samples, n_features)
  
  Returns
  -------
  X : array
      Return the transformed training data
  
  Notes
  -----
  Please see the `scikit-learn API documentation
  <https://scikit-learn.org/stable/developers/develop.html#apis-of-scikit-learn-objects>`_
  for further information.
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code: def transform(self, X):
      """The transform function calls the transform function of the
      underlying scikit-learn model and returns the transformed array.
  
      Parameters
      ----------
      X : array-like, shape = (n_samples, n_features)
  
      Returns
      -------
      X : array
          Return the transformed training data
  
      Notes
      -----
      Please see the `scikit-learn API documentation
      <https://scikit-learn.org/stable/developers/develop.html#apis-of-scikit-learn-objects>`_
      for further information."""
      raise NotImplementedError()
  
imports: from typing import Dict, Optional
  import importlib
  import inspect
  import pkgutil
  import sys
  from collections import OrderedDict
  from sklearn.base import BaseEstimator, TransformerMixin
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.constants import SPARSE
label_desc: Use image node_id 2 for calling the AutoSklearnPreprocessingAlgorithm obj's underlying member method code with example usage: obj.transform(X) without return types