code: def test_RandomForest(self):
      model = RandomForestClassifier(n_estimators=4, max_depth=6)
      model.fit(self.x_train, np.argmax(self.y_train, axis=1))
  
      classifier = SklearnClassifier(model=model)
  
      rt = RobustnessVerificationTreeModelsCliqueMethod(
          classifier=classifier, verbose=False
      )
      average_bound, verified_error = rt.verify(
          x=self.x_test,
          y=self.y_test,
          eps_init=0.3,
          nb_search_steps=10,
          max_clique=2,
          max_level=2,
      )
  
      self.assertEqual(average_bound, 0.016482421874999993)
      self.assertEqual(verified_error, 1.0)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  from xgboost import XGBClassifier
  import lightgbm
  import numpy
  from sklearn.ensemble import ExtraTreesClassifier, RandomForestClassifier, GradientBoostingClassifier
  from art.estimators.classification.xgboost import XGBoostClassifier
  from art.estimators.classification.lightgbm import LightGBMClassifier
  from art.estimators.classification.scikitlearn import SklearnClassifier
  from art.utils import load_dataset
  from art.metrics.verification_decisions_trees import RobustnessVerificationTreeModelsCliqueMethod
  from tests.utils import master_seed
label_desc: Use image node_id 6 for calling the TestMetricsTrees obj's underlying member method code with example usage: obj.test_RandomForest() without return types