class_docstr: Defines the ErrorReport, which contains the tree and matrix filter.
  
  :param tree: The representation of the tree.
  :type tree: dict
  :param matrix: The representation of the matrix filter.
  :type matrix: dict
  :param id: The unique identifier for the ErrorReport.
      A new unique id is created if none is specified.
  :type id: str
class_docstr_tok: ["Defines","the","ErrorReport",",","which","contains","the","tree","and","matrix","filter",".",":","param","tree",":","The","representation","of","the","tree",".",":","type","tree",":","dict",":","param","matrix",":","The","representation","of","the","matrix","filter",".",":","type","matrix",":","dict",":","param","id",":","The","unique","identifier","for","the","ErrorReport",".","A","new","unique","id","is","created","if","none","is","specified",".",":","type","id",":","str"]
docstr: Returns the features that were selected to train tree.
  
  The features are used to train the surrogate decision
  tree on errors.
  
  :return: The features selected to train tree.
  :rtype: list[str]
docstr_tok: ["Returns","the","features","that","were","selected","to","train","tree",".","The","features","are","used","to","train","the","surrogate","decision","tree","on","errors",".",":","return",":","The","features","selected","to","train","tree",".",":","rtype",":","list","[","str","]"]
code: def tree_features(self):
      """Returns the features that were selected to train tree.
  
      The features are used to train the surrogate decision
      tree on errors.
  
      :return: The features selected to train tree.
      :rtype: list[str]
      """
      return self._tree_features
  
file_path: responsible-ai-toolbox/erroranalysis/erroranalysis/report/error_report.py
imports: import json
  import uuid
  from raiutils.data_processing import serialize_json_safe
label_desc: Use image node_id 5 for calling the ErrorReport obj's underlying member method code with example usage: obj.tree_features() and returns: self