class_docstr: Implementation of methods in Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks.
  Wang et al. (2019).
  
  | Paper link: https://people.cs.uchicago.edu/~ravenben/publications/pdf/backdoor-sp19.pdf
docstr: Mitigates the effect of poison on a classifier
  
  :param x_val: Validation data to use to mitigate the effect of poison.
  :param y_val: Validation labels to use to mitigate the effect of poison.
  :param mitigation_types: The types of mitigation method, can include 'unlearning', 'pruning', or 'filtering'
  :return: Tuple of length 2 of the selected class and certified radius.
docstr_tok: ["Mitigates","the","effect","of","poison","on","a","classifier",":","param","x_val",":","Validation","data","to","use","to","mitigate","the","effect","of","poison",".",":","param","y_val",":","Validation","labels","to","use","to","mitigate","the","effect","of","poison",".",":","param","mitigation_types",":","The","types","of","mitigation","method",",","can","include","'unlearning","'",",","'pruning","'",",","or","'filtering'",":","return",":","Tuple","of","length","2","of","the","selected","class","and","certified","radius","."]
code: def mitigate(
      self,
      x_val: np.ndarray,
      y_val: np.ndarray,
      mitigation_types: List[str],
  ) -> None:
      """
      Mitigates the effect of poison on a classifier
  
      :param x_val: Validation data to use to mitigate the effect of poison.
      :param y_val: Validation labels to use to mitigate the effect of poison.
      :param mitigation_types: The types of mitigation method, can include 'unlearning', 'pruning', or 'filtering'
      :return: Tuple of length 2 of the selected class and certified radius.
      """
      return NeuralCleanseMixin.mitigate(
          self, x_val, y_val, mitigation_types
      )
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from tqdm.auto import tqdm
  from art.config import ART_NUMPY_DTYPE
  from art.estimators.poison_mitigation.neural_cleanse.neural_cleanse import NeuralCleanseMixin
  from art.estimators.classification.keras import KerasClassifier, KERAS_MODEL_TYPE
label_desc: Use image node_id 10 for calling the KerasNeuralCleanse obj's underlying member method code with example usage: obj.mitigate(x_val, y_val, mitigation_types) and returns: NeuralCleanseMixin