code: def fit(self, X, y):
      counts = Counter(y)
      max_count = -1
      for label, count in counts.items():
          if count > max_count:
              self.majority_class = label
              max_count = count
      return self
  
file_path: skll/tests/other/majority_class_learner.py
imports: from collections import Counter
  import numpy
  from sklearn.base import BaseEstimator, ClassifierMixin
label_desc: Use image node_id 2 for calling the MajorityClassLearner obj's underlying member method code with example usage: obj.fit(X, y) and returns: self