class_docstr: A processing interface for labeling tokens with zero or more
  category labels (or "labels").  Labels are typically strs
  or ints, but can be any immutable type.  The set of labels
  that the multi-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)
class_docstr_tok: ["A","processing","interface","for","labeling","tokens","with","zero","or","more","category","labels","(","or","``","labels","''",")",".","Labels","are","typically","strs","or","ints",",","but","can","be","any","immutable","type",".","The","set","of","labels","that","the","multi-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",")"]
docstr: Apply ``self.prob_classify()`` to each element of ``featuresets``.  I.e.:
  
      return [self.prob_classify(fs) for fs in featuresets]
  
  :rtype: list(ProbDistI)
docstr_tok: ["Apply","``","self.prob_classify","(",")","``","to","each","element","of","``","featuresets","``",".","I.e",".",":","return","[","self.prob_classify","(","fs",")","for","fs","in","featuresets","]",":","rtype",":","list","(","ProbDistI",")"]
code: def prob_classify_many(self, featuresets):
      """
      Apply ``self.prob_classify()`` to each element of ``featuresets``.  I.e.:
  
          return [self.prob_classify(fs) for fs in featuresets]
  
      :rtype: list(ProbDistI)
      """
      return [self.prob_classify(fs) for fs in featuresets]
  
file_path: nltk/nltk/classify/api.py
imports: from nltk.internals import overridden
label_desc: Use image node_id 5 for calling the MultiClassifierI obj's underlying member method code with example usage: obj.prob_classify_many(featuresets) and returns: unknown