class_docstr: Term-Frequency document model (term = word).
class_docstr_tok: ["Term-Frequency","document","model","(","term","=","word",")","."]
docstr: Returns ``count`` of terms sorted by their frequency
  in descending order.
  
  :parameter int count:
      Max. number of returned terms. Value 0 means no limit (default).
docstr_tok: ["Returns","``","count","``","of","terms","sorted","by","their","frequency","in","descending","order",".",":","parameter","int","count",":","Max",".","number","of","returned","terms",".","Value","0","means","no","limit","(","default",")","."]
code: def most_frequent_terms(self, count=0):
      """
      Returns ``count`` of terms sorted by their frequency
      in descending order.
  
      :parameter int count:
          Max. number of returned terms. Value 0 means no limit (default).
      """
      # sort terms by number of occurrences in descending order
      terms = sorted(self._terms.items(), key=lambda i: -i[1])
  
      terms = tuple(i[0] for i in terms)
      if count == 0:
          return terms
      elif count > 0:
          return terms[:count]
      else:
          raise ValueError(
              "Only non-negative values are allowed for count of terms."
          )
  
file_path: sumy/sumy/models/tf.py
imports: from __future__ import absolute_import
  from __future__ import division, print_function, unicode_literals
  import math
  from collections import Counter
  from pprint import pformat
  from .._compat import to_unicode, unicode, string_types, Sequence
label_desc: Use image node_id 4 for calling the TfDocumentModel obj's underlying member method code with example usage: obj.most_frequent_terms(count) and returns: terms, terms