code: def majority_voting_rule(votes):
      """Applies the majority voting rule to the estimated votes.
  
      Parameters
      ----------
      votes : array of shape (n_samples, n_classifiers),
          The votes obtained by each classifier for each sample.
  
      Returns
      -------
      predicted_label : array of shape (n_samples)
          The label of each query sample predicted using the majority voting rule
      """
      # Omitting nan value in the predictions as they comes from removed
      # classifiers
      return mode(votes, axis=1)[0][:, 0]
  
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 4 for calling a global function with example usage: majority_voting_rule(votes) and returns: mode