code: def maximization(scores):
      """Combination method to merge the scores from multiple estimators
      by taking the maximum.
  
      Parameters
      ----------
      scores : numpy array of shape (n_samples, n_estimators)
          Score matrix from multiple estimators on the same samples.
  
      Returns
      -------
      combined_scores : numpy array of shape (n_samples, )
          The combined scores.
  
      """
  
      scores = check_array(scores)
      return np.max(scores, axis=1).ravel()
  
file_path: combo/combo/models/score_comb.py
imports: import numpy
  from numpy.random import RandomState
  from sklearn.utils import check_array
  from sklearn.utils import column_or_1d
  from sklearn.utils import shuffle
  from sklearn.utils.extmath import weighted_mode
  from sklearn.utils.random import sample_without_replacement
  from numpy.testing import assert_equal
  from sklearn.utils.multiclass import check_classification_targets
  from pyod.utils.utility import check_parameter
label_desc: Use image node_id 5 for calling a global function with example usage: maximization(scores) and returns: np