class_docstr: Robustness verification for decision-tree-based models.
  Following the implementation in https://github.com/chenhongge/treeVerification (MIT License, 9 August 2019)
  
  | Paper link: https://arxiv.org/abs/1906.03849
docstr: Create robustness verification for a decision-tree-based classifier.
  
  :param classifier: A trained decision-tree-based classifier.
  :param verbose: Show progress bars.
docstr_tok: ["Create","robustness","verification","for","a","decision-tree-based","classifier",".",":","param","classifier",":","A","trained","decision-tree-based","classifier",".",":","param","verbose",":","Show","progress","bars","."]
code: def __init__(
      self, classifier: "ClassifierDecisionTree", verbose: bool = True
  ) -> None:
      """
      Create robustness verification for a decision-tree-based classifier.
  
      :param classifier: A trained decision-tree-based classifier.
      :param verbose: Show progress bars.
      """
      self._classifier = classifier
      self.verbose = verbose
      self._trees = self._classifier.get_trees()
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import Dict, List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from tqdm.auto import trange
  from art.utils import check_and_transform_label_format
label_desc: Use image node_id 1 to create a new RobustnessVerificationTreeModelsCliqueMethod object  with example: obj = RobustnessVerificationTreeModelsCliqueMethod(classifier, verbose)