class_docstr: Close implementation of Papernot's attack on decision trees following Algorithm 2 and communication with the
  authors.
  
  | Paper link: https://arxiv.org/abs/1605.07277
docstr: :param classifier: A trained scikit-learn decision tree model.
  :param offset: How much the value is pushed away from tree's threshold.
  :param verbose: Show progress bars.
docstr_tok: [":","param","classifier",":","A","trained","scikit-learn","decision","tree","model",".",":","param","offset",":","How","much","the","value","is","pushed","away","from","tree","'s","threshold",".",":","param","verbose",":","Show","progress","bars","."]
code: def __init__(
      self,
      classifier: ScikitlearnDecisionTreeClassifier,
      offset: float = 0.001,
      verbose: bool = True,
  ) -> None:
      """
      :param classifier: A trained scikit-learn decision tree model.
      :param offset: How much the value is pushed away from tree's threshold.
      :param verbose: Show progress bars.
      """
      super().__init__(estimator=classifier)
      self.offset = offset
      self.verbose = verbose
      self._check_params()
  
file_path: adversarial-robustness-toolbox/art/attacks/evasion/decision_tree_attack.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import List, Optional, Union
  import numpy
  from tqdm.auto import trange
  from art.attacks.attack import EvasionAttack
  from art.estimators.classification.scikitlearn import ScikitlearnDecisionTreeClassifier
  from art.utils import check_and_transform_label_format
label_desc: Use image node_id 1 to create a new DecisionTreeAttack object from inherited base classes: EvasionAttack with example: obj = DecisionTreeAttack(classifier, offset, verbose)