class_docstr: A processing interface for labeling tokens with a single category
  label (or "class").  Labels are typically strs or
  ints, but can be any immutable type.  The set of labels
  that the classifier chooses from must be fixed and finite.
  
  Subclasses must define:
    - ``labels()``
    - either ``classify()`` or ``classify_many()`` (or both)
  
  Subclasses may define:
    - either ``prob_classify()`` or ``prob_classify_many()`` (or both)
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docstr: :return: a probability distribution over labels for the given
      featureset.
  :rtype: ProbDistI
docstr_tok: [":","return",":","a","probability","distribution","over","labels","for","the","given","featureset",".",":","rtype",":","ProbDistI"]
code: def prob_classify(self, featureset):
      """
      :return: a probability distribution over labels for the given
          featureset.
      :rtype: ProbDistI
      """
      if overridden(self.prob_classify_many):
          return self.prob_classify_many([featureset])[0]
      else:
          raise NotImplementedError()
  
file_path: nltk/nltk/classify/api.py
imports: from nltk.internals import overridden
label_desc: Use image node_id 3 for calling the ClassifierI obj's underlying member method code with example usage: obj.prob_classify(featureset) and returns: self