class_docstr: Reduce corpus to the X most important terms.  Great for plotting a big corpus.
  Will return between X/2 and X terms.
  
  Returns the terms with the X highest absolute scores, background corpus scores, and term frequencies.
docstr: Parameters
  ----------
  term_doc_matrix: TermDocMatrix or descendant
  scores: array-like
          Same length as number of terms in TermDocMatrix.
  num_term_to_keep: int, default=4000.
          Should be> 0. Number of terms to keep. Will keep between num_terms_to_keep/2 and num_terms_to_keep.
  
  Returns
  -------
  set, terms that should be shown
docstr_tok: ["Parameters","--","--","--","--","--","term_doc_matrix",":","TermDocMatrix","or","descendant","scores",":","array-like","Same","length","as","number","of","terms","in","TermDocMatrix",".","num_term_to_keep",":","int",",","default=4000",".","Should","be",">","0",".","Number","of","terms","to","keep",".","Will","keep","between","num_terms_to_keep\/2","and","num_terms_to_keep",".","Returns","--","--","--","-","set",",","terms","that","should","be","shown"]
code: def get_selected_terms(
      term_doc_matrix, scores, num_term_to_keep=None
  ):
      """
      Parameters
      ----------
      term_doc_matrix: TermDocMatrix or descendant
      scores: array-like
              Same length as number of terms in TermDocMatrix.
      num_term_to_keep: int, default=4000.
              Should be> 0. Number of terms to keep. Will keep between num_terms_to_keep/2 and num_terms_to_keep.
  
      Returns
      -------
      set, terms that should be shown
      """
      num_term_to_keep = (
          AutoTermSelector._add_default_num_terms_to_keep(
              num_term_to_keep
          )
      )
      term_doc_freq = term_doc_matrix.get_term_freq_df()
      term_doc_freq["count"] = term_doc_freq.sum(axis=1)
      term_doc_freq["score"] = scores
      score_terms = AutoTermSelector._get_score_terms(
          num_term_to_keep, term_doc_freq
      )
      background_terms = AutoTermSelector._get_background_terms(
          num_term_to_keep, term_doc_matrix
      )
      frequent_terms = AutoTermSelector._get_frequent_terms(
          num_term_to_keep, term_doc_freq
      )
      terms_to_show = score_terms.union(background_terms).union(
          frequent_terms
      )
      return terms_to_show
  
label_desc: Use image node_id 2 for calling the AutoTermSelector obj's underlying member method code with example usage: obj.get_selected_terms(term_doc_matrix, scores, num_term_to_keep) and returns: terms_to_show