code: def test_decision_function():
      np.random.seed(123)
  
      # PassiveAggressiveClassifier has no predict_proba
      meta = PassiveAggressiveClassifier(random_state=42)
      clf1 = RandomForestClassifier(n_estimators=10)
      clf2 = GaussianNB()
      sclf = StackingCVClassifier(
          classifiers=[clf1, clf2],
          use_probas=True,
          meta_classifier=meta,
      )
  
      scores = cross_val_score(
          sclf, X_breast, y_breast, cv=5, scoring="roc_auc"
      )
      scores_mean = round(scores.mean(), 2)
      assert scores_mean == 0.96, scores_mean
  
      # another test
      meta = SVC(decision_function_shape="ovo")
  
      sclf = StackingCVClassifier(
          classifiers=[clf1, clf2],
          use_probas=True,
          meta_classifier=meta,
      )
  
      scores = cross_val_score(
          sclf, X_breast, y_breast, cv=5, scoring="roc_auc"
      )
      scores_mean = round(scores.mean(), 2)
  
      if Version(sklearn_version) < Version("0.21"):
          assert scores_mean == 0.94, scores_mean
      elif Version(sklearn_version) < Version("0.22"):
          assert scores_mean == 0.96, scores_mean
      else:
          assert scores_mean == 0.90, scores_mean
  
imports: import random
  import numpy
  import pandas
  import pytest
  from packaging.version import Version
  from scipy import sparse
  from sklearn import __version__
  from sklearn import datasets, exceptions
  from sklearn.base import clone
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import LogisticRegression, PassiveAggressiveClassifier
  from sklearn.metrics import roc_auc_score
  from sklearn.model_selection import GridSearchCV, KFold, cross_val_score, train_test_split
  from sklearn.naive_bayes import GaussianNB
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.svm import SVC
  from mlxtend.classifier import StackingCVClassifier
  from mlxtend.data import iris_data
  from mlxtend.externals.estimator_checks import NotFittedError
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 26 for calling a global function with example usage: test_decision_function() without return types