class_docstr: An abstract class that wraps around the nltk.classify module.
  
  Expects that descendant classes include a class variable ``nltk_class``
  which is the class in the nltk.classify module to be wrapped.
  
  Example: ::
  
      class MyClassifier(NLTKClassifier):
          nltk_class = nltk.classify.svm.SvmClassifier
class_docstr_tok: ["An","abstract","class","that","wraps","around","the","nltk.classify","module",".","Expects","that","descendant","classes","include","a","class","variable","``","nltk_class","``","which","is","the","class","in","the","nltk.classify","module","to","be","wrapped",".","Example",":",":",":","class","MyClassifier","(","NLTKClassifier",")",":","nltk_class","=","nltk.classify.svm.SvmClassifier"]
docstr: Classifies the text.
  
  :param str text: A string of text.
docstr_tok: ["Classifies","the","text",".",":","param","str","text",":","A","string","of","text","."]
code: def classify(self, text):
      """Classifies the text.
  
      :param str text: A string of text.
      """
      text_features = self.extract_features(text)
      return self.classifier.classify(text_features)
  
imports: from __future__ import absolute_import
  from itertools import chain
  import nltk
  from textblob.compat import basestring
  from textblob.decorators import cached_property
  from textblob.exceptions import FormatError
  from textblob.tokenizers import word_tokenize
  from textblob.utils import strip_punc, is_filelike
  import textblob.formats
label_desc: Use image node_id 6 for calling the NLTKClassifier obj's underlying member method code with example usage: obj.classify(text) and returns: self