code: def aom(
      scores,
      n_buckets=5,
      method="static",
      bootstrap_estimators=False,
      random_state=None,
  ):
      """Average of Maximum - An ensemble method for combining multiple
      estimators. See :cite:`aggarwal2015theoretical` for details.
  
      First dividing estimators into subgroups, take the maximum score as the
      subgroup score. Finally, take the average of all subgroup outlier scores.
  
      Parameters
      ----------
      scores : numpy array of shape (n_samples, n_estimators)
          The score matrix outputted from various estimators
  
      n_buckets : int, optional (default=5)
          The number of subgroups to build
  
      method : str, optional (default='static')
          {'static', 'dynamic'}, if 'dynamic', build subgroups
          randomly with dynamic bucket size.
  
      bootstrap_estimators : bool, optional (default=False)
          Whether estimators are drawn with replacement.
  
      random_state : int, RandomState instance or None, optional (default=None)
          If int, random_state is the seed used by the
          random number generator; If RandomState instance, random_state is
          the random number generator; If None, the random number generator
          is the RandomState instance used by `np.random`.
  
      Returns
      -------
      combined_scores : Numpy array of shape (n_samples,)
          The combined outlier scores.
  
      """
  
      return combo_aom(
          scores, n_buckets, method, bootstrap_estimators, random_state
      )
  
file_path: pyod/pyod/models/combination.py
imports: from __future__ import division
  from __future__ import print_function
  from combo.models.score_comb import aom
  from combo.models.score_comb import moa
  from combo.models.score_comb import average
  from combo.models.score_comb import maximization
  from combo.models.score_comb import majority_vote
  from combo.models.score_comb import median
label_desc: Use image node_id 1 for calling a global function with example usage: aom(scores, n_buckets, method, bootstrap_estimators, random_state) and returns: combo_aom