docstr: Limit terms to ones that make up a minimum percentage
  of documents in a category.  Given a term_count, set the threshold
  to that of the smallest class.
  
  Parameters
  ----------
  term_ranker : TermRanker
  term_count : int
docstr_tok: ["Limit","terms","to","ones","that","make","up","a","minimum","percentage","of","documents","in","a","category",".","Given","a","term_count",",","set","the","threshold","to","that","of","the","smallest","class",".","Parameters","--","--","--","--","--","term_ranker",":","TermRanker","term_count",":","int"]
code: def __init__(self, term_ranker=AbsoluteFrequencyRanker, term_count=2):
      """
      Limit terms to ones that make up a minimum percentage
      of documents in a category.  Given a term_count, set the threshold
      to that of the smallest class.
  
      Parameters
      ----------
      term_ranker : TermRanker
      term_count : int
      """
      self.term_ranker = term_ranker
      self.term_count = term_count
  
imports: import numpy
  from scattertext.termranking import AbsoluteFrequencyRanker
label_desc: Use image node_id 1 to create a new ClassPercentageCompactor object from inherited base classes: object with example: obj = ClassPercentageCompactor(term_ranker, term_count)