code: def setUp(self):
      self.roc_floor = 0.9
      self.accuracy_floor = 0.9
  
      random_state = 42
      X, y = load_breast_cancer(return_X_y=True)
  
      (
          self.X_train,
          self.X_test,
          self.y_train,
          self.y_test,
      ) = train_test_split(
          X, y, test_size=0.4, random_state=random_state
      )
  
      classifiers = [
          DecisionTreeClassifier(random_state=random_state),
          LogisticRegression(random_state=random_state),
          KNeighborsClassifier(),
          RandomForestClassifier(random_state=random_state),
          GradientBoostingClassifier(random_state=random_state),
      ]
  
      self.clf = SimpleClassifierAggregator(
          classifiers, method="majority_vote"
      )
      self.clf.fit(self.X_train, self.y_train)
  
imports: import os
  import sys
  import unittest
  import numpy
  from sklearn.model_selection import train_test_split
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import GradientBoostingClassifier
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.datasets import load_breast_cancer
  from numpy.testing import assert_allclose
  from numpy.testing import assert_equal
  from numpy.testing import assert_raises
  from sklearn.metrics import roc_auc_score
  from sklearn.metrics import accuracy_score
  from combo.models.classifier_comb import SimpleClassifierAggregator
  from combo.utils.data import evaluate_print
label_desc: Use image node_id 1 for calling the TestMajorityVote obj's underlying member method code with example usage: obj.setUp() without return types