code: def maximum_combiner(classifier_ensemble, X):
      """Ensemble combination using the Maximum rule.
  
      Parameters
      ----------
      classifier_ensemble : list of shape = [n_classifiers]
          Containing the ensemble of classifiers used in the aggregation scheme.
  
      X : array of shape (n_samples, n_features)
          The input data.
  
      Returns
      -------
      predicted_label : array of shape (n_samples)
          The label of each query sample predicted using the majority voting rule
      """
      ensemble_proba = _get_ensemble_probabilities(
          classifier_ensemble, X
      )
      return maximum_rule(ensemble_proba)
  
imports: import numpy
  from scipy.stats.mstats import mode
  from sklearn.utils.validation import check_array
  from deslib.util.prob_functions import softmax
label_desc: Use image node_id 13 for calling a global function with example usage: maximum_combiner(classifier_ensemble, X) and returns: maximum_rule