class_docstr: This is the Auditor class. It is used in the training algorithm to repeatedly find subgroups that break the
  fairness disparity constraint. You can also use it independently as a stand alone auditor.
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docstr: Takes in predictions on dataset (X',y) and returns:
  a membership vector which represents the group that violates the fairness metric,
  along with the gamma disparity.
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code: def audit(self, predictions):
      """Takes in predictions on dataset (X',y) and returns:
      a membership vector which represents the group that violates the fairness metric,
      along with the gamma disparity.
      """
      if isinstance(predictions, pd.DataFrame):
          predictions = predictions.values
  
      metric_baseline = self.get_baseline(self.y_input, predictions)
      group = self.get_group(predictions, metric_baseline)
  
      return group.func.predict(self.X_prime), group.weighted_disparity
  
file_path: AIF360/aif360/algorithms/inprocessing/gerryfair/auditor.py
imports: import numpy
  import pandas
  from sklearn import linear_model
  from aif360.algorithms.inprocessing.gerryfair.reg_oracle_class import RegOracle
  from aif360.algorithms.inprocessing.gerryfair import clean
label_desc: Use image node_id 7 for calling the Auditor obj's underlying member method code with example usage: obj.audit(predictions) and returns: group,  group