code: def setUp(self):
      self.n_train = 200
      self.n_test = 100
      self.contamination = 0.1
      self.roc_floor = 0.8
      (
          self.X_train,
          self.X_test,
          self.y_train,
          self.y_test,
      ) = generate_data(
          n_train=self.n_train,
          n_test=self.n_test,
          behaviour="new",
          contamination=self.contamination,
          random_state=42,
      )
  
      detectors = [KNN(), LOF(), OCSVM()]
  
      self.clf = SimpleDetectorAggregator(
          base_estimators=detectors,
          method="maximization",
          contamination=self.contamination,
      )
      self.clf.fit(self.X_train)
  
imports: import os
  import sys
  import numpy
  import unittest
  from numpy.testing import assert_equal
  from numpy.testing import assert_raises
  from sklearn.metrics import roc_auc_score
  from pyod.utils.data import generate_data
  from pyod.models.knn import KNN
  from pyod.models.lof import LOF
  from pyod.models.ocsvm import OCSVM
  from combo.models.detector_comb import SimpleDetectorAggregator
label_desc: Use image node_id 1 for calling the Maximization obj's underlying member method code with example usage: obj.setUp() without return types