class_docstr: Wraps an instance of an :obj:`art.classifiers.Classifier` to extend
  :obj:`~aif360.algorithms.Transformer`.
docstr: Train a classifer on the input.
  
  Args:
      dataset (Dataset): Training dataset.
      batch_size (int): Size of batches (passed through to ART).
      nb_epochs (int): Number of epochs to use for training (passed
          through to ART).
  
  Returns:
      ARTClassifier: Returns self.
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code: def fit(self, dataset, batch_size=128, nb_epochs=20):
      """Train a classifer on the input.
  
      Args:
          dataset (Dataset): Training dataset.
          batch_size (int): Size of batches (passed through to ART).
          nb_epochs (int): Number of epochs to use for training (passed
              through to ART).
  
      Returns:
          ARTClassifier: Returns self.
      """
      self._art_classifier.fit(
          dataset.features,
          dataset.labels,
          batch_size=batch_size,
          nb_epochs=nb_epochs,
      )
      return self
  
imports: import numpy
  from aif360.datasets import BinaryLabelDataset
  from aif360.algorithms import Transformer
label_desc: Use image node_id 2 for calling the ARTClassifier obj's underlying member method code with example usage: obj.fit(dataset, batch_size, nb_epochs) and returns: self