docstr: Specify the category to score. Optionally, score against a specific set of categories.
docstr_tok: ["Specify","the","category","to","score",".","Optionally",",","score","against","a","specific","set","of","categories","."]
code: def set_categories(
      self,
      category_name,
      not_category_names=[],
      neutral_category_names=[],
  ):
      """
      Specify the category to score. Optionally, score against a specific set of categories.
      """
  
      tdf = self.term_ranker_.set_non_text(
          non_text=self.use_metadata_
      ).get_ranks()
      d = {"cat": tdf[str(category_name) + " freq"]}
      if not_category_names == []:
          not_category_names = [
              str(c) + " freq"
              for c in self.corpus_.get_categories()
              if c != category_name
          ]
      else:
          not_category_names = [
              str(c) + " freq" for c in not_category_names
          ]
      d["ncat"] = tdf[not_category_names].sum(axis=1)
      if neutral_category_names == []:
          # neutral_category_names = [c + ' freq' for c in self.corpus.get_categories()
          #                          if c != category_name and c not in not_category_names]
          pass
      else:
          neutral_category_names = [
              str(c) + " freq" for c in neutral_category_names
          ]
      for i, c in enumerate(neutral_category_names):
          d["neut%s" % (i)] = tdf[c]
      self.tdf_ = pd.DataFrame(d)
      self.category_name = category_name
      self.not_category_names = [c[:-5] for c in not_category_names]
      self.neutral_category_names = [
          c[:-5] for c in neutral_category_names
      ]
      self.category_name_is_set_ = True
      return self
  
imports: from abc import ABCMeta, abstractmethod
  from typing import Tuple
  import numpy
  import pandas
  from scattertext.ParsedCorpus import ParsedCorpus
  from scipy import stats
  from scipy.sparse import vstack
  from scattertext.util import inherits_from
  from scattertext.termranking import AbsoluteFrequencyRanker
  from scattertext.termranking.TermRanker import TermRanker
label_desc: Use image node_id 13 for calling the CorpusBasedTermScorer obj's underlying member method code with example usage: obj.set_categories(category_name, not_category_names, neutral_category_names) and returns: self