class_docstr: Implementation of the High-Confidence-Low-Uncertainty (HCLU) adversarial example formulation by Grosse et al. (2018)
  
  | Paper link: https://arxiv.org/abs/1812.02606
docstr: :param classifier: A trained model of type GPYGaussianProcessClassifier.
  :param conf: Confidence that examples should have, if there were to be classified as 1.0 maximally.
  :param unc_increase: Value uncertainty is allowed to deviate, where 1.0 is original value.
  :param min_val: minimal value any feature can take.
  :param max_val: maximal value any feature can take.
  :param verbose: Show progress bars.
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code: def __init__(
      self,
      classifier: GPyGaussianProcessClassifier,
      conf: float = 0.95,
      unc_increase: float = 100.0,
      min_val: float = 0.0,
      max_val: float = 1.0,
      verbose: bool = True,
  ) -> None:
      """
      :param classifier: A trained model of type GPYGaussianProcessClassifier.
      :param conf: Confidence that examples should have, if there were to be classified as 1.0 maximally.
      :param unc_increase: Value uncertainty is allowed to deviate, where 1.0 is original value.
      :param min_val: minimal value any feature can take.
      :param max_val: maximal value any feature can take.
      :param verbose: Show progress bars.
      """
      super().__init__(estimator=classifier)
      self.conf = conf
      self.unc_increase = unc_increase
      self.min_val = min_val
      self.max_val = max_val
      self.verbose = verbose
      self._check_params()
  
file_path: adversarial-robustness-toolbox/art/attacks/evasion/hclu.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import copy
  import logging
  from typing import Optional
  import numpy
  from scipy.optimize import minimize
  from tqdm.auto import trange
  from art.attacks.attack import EvasionAttack
  from art.estimators.classification.GPy import GPyGaussianProcessClassifier
label_desc: Use image node_id 1 to create a new HighConfidenceLowUncertainty object from inherited base classes: EvasionAttack with example: obj = HighConfidenceLowUncertainty(classifier, conf, unc_increase, min_val, max_val, verbose)