class_docstr: Feature Importance
class_docstr_tok: ["Feature","Importance"]
docstr: Add information of feature importance to the report.
  
  Args:
      importance_ranking(:list of :list): a list of 2-item lists,
                              item[0]: score, item[1] feature_name
      importance_threshold(float): threshold for displaying the
                                  feature name and score in tables
      maximum_number_feature(int): maximum number of features shown in bar-chart diagram
      notes(str): text to explain the block
docstr_tok: ["Add","information","of","feature","importance","to","the","report",".","Args",":","importance_ranking","(",":","list","of",":","list",")",":","a","list","of","2-item","lists",",","item","[","0","]",":","score",",","item","[","1","]","feature_name","importance_threshold","(","float",")",":","threshold","for","displaying","the","feature","name","and","score","in","tables","maximum_number_feature","(","int",")",":","maximum","number","of","features","shown","in","bar-chart","diagram","notes","(","str",")",":","text","to","explain","the","block"]
code: def __init__(
      self,
      importance_ranking: List[List],
      importance_threshold: float,
      maximum_number_feature=20,
      notes=None,
  ) -> None:
      """
      Add information of feature importance to the report.
  
      Args:
          importance_ranking(:list of :list): a list of 2-item lists,
                                  item[0]: score, item[1] feature_name
          importance_threshold(float): threshold for displaying the
                                      feature name and score in tables
          maximum_number_feature(int): maximum number of features shown in bar-chart diagram
          notes(str): text to explain the block
      """
      super(FeatureImportance, self).__init__(
          importance_ranking,
          importance_threshold,
          maximum_number_feature,
          notes,
      )
      self._importance_ranking = importance_ranking
      self._importance_threshold = importance_threshold
      self._maximum_number_feature = maximum_number_feature
      self._notes = notes
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import List, Tuple
  import numpy
  from xai.formatter.contents.base import Content
  from xai.formatter.writer.base import Writer
label_desc: Use image node_id 1 to create a new FeatureImportance object from inherited base classes: Content with example: obj = FeatureImportance(importance_ranking, importance_threshold, maximum_number_feature, notes)