class_docstr: Implementation of a simple, rule-based black-box membership inference attack.
  
  This implementation uses the simple rule: if the model's prediction for a sample is correct, then it is a
  member. Otherwise, it is not a member.
docstr: Create a MembershipInferenceBlackBoxRuleBased attack instance.
  
  :param classifier: Target classifier.
code: def __init__(self, classifier: "CLASSIFIER_TYPE"):
      """
      Create a MembershipInferenceBlackBoxRuleBased attack instance.
  
      :param classifier: Target classifier.
      """
      super().__init__(estimator=classifier)
  
file_path: adversarial-robustness-toolbox/art/attacks/inference/membership_inference/black_box_rule_based.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import Optional, TYPE_CHECKING
  import numpy
  from art.attacks.attack import MembershipInferenceAttack
  from art.estimators.estimator import BaseEstimator
  from art.estimators.classification.classifier import ClassifierMixin
  from art.utils import check_and_transform_label_format
label_desc: Use image node_id 1 to create a new MembershipInferenceBlackBoxRuleBased object from inherited base classes: MembershipInferenceAttack with example: obj = MembershipInferenceBlackBoxRuleBased(classifier)