class_docstr: Random forest attacker.
code: def __init__(self, backend: Optional[str] = None):
      super().__init__(backend=backend)
  
imports: import contextlib
  import dataclasses
  import logging
  from typing import Optional
  import numpy
  from sklearn import ensemble
  from sklearn import linear_model
  from sklearn import model_selection
  from sklearn import neighbors
  from sklearn import neural_network
  from sklearn.utils import parallel_backend
  from tensorflow_privacy.privacy.privacy_tests.membership_inference_attack import data_structures
label_desc: Use image node_id 1 to create a new RandomForestAttacker object from inherited base classes: TrainedAttacker with example: obj = RandomForestAttacker(backend)