code: def test_decision_function():
      np.random.seed(123)
  
      # PassiveAggressiveClassifier has no predict_proba
      meta = PassiveAggressiveClassifier(
          max_iter=1000, tol=0.001, random_state=42
      )
      clf1 = RandomForestClassifier(n_estimators=10)
      clf2 = GaussianNB()
      sclf = StackingClassifier(
          classifiers=[clf1, clf2],
          use_probas=True,
          meta_classifier=meta,
      )
  
      # binarize target
      y2 = y > 1
      scores = cross_val_score(sclf, X, y2, cv=5, scoring="roc_auc")
      scores_mean = round(scores.mean(), 2)
  
      if Version(sklearn_version) < Version("0.21"):
          assert scores_mean == 0.96, scores_mean
      else:
          assert scores_mean == 0.93, scores_mean
  
      # another test
      meta = SVC(decision_function_shape="ovo")
  
      sclf = StackingClassifier(
          classifiers=[clf1, clf2],
          use_probas=True,
          meta_classifier=meta,
      )
  
      scores = cross_val_score(sclf, X, y2, cv=5, scoring="roc_auc")
      scores_mean = round(scores.mean(), 2)
  
      if Version(sklearn_version) < Version("0.22"):
          assert scores_mean == 0.95, scores_mean
      else:
          assert scores_mean == 0.94, scores_mean
  
imports: import random
  import numpy
  import pytest
  from numpy.testing import assert_almost_equal
  from packaging.version import Version
  from scipy import sparse
  from sklearn import __version__
  from sklearn import exceptions
  from sklearn.base import clone
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import LogisticRegression, PassiveAggressiveClassifier
  from sklearn.model_selection import GridSearchCV, 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 StackingClassifier
  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