code: def test_get_params():
      clf1 = KNeighborsClassifier(n_neighbors=1)
      clf2 = RandomForestClassifier(random_state=1)
      clf3 = GaussianNB()
      lr = LogisticRegression(multi_class="ovr", solver="liblinear")
      sclf = StackingCVClassifier(
          classifiers=[clf1, clf2, clf3], meta_classifier=lr
      )
  
      got = sorted(
          list({s.split("__")[0] for s in sclf.get_params().keys()})
      )
  
      expect = [
          "classifiers",
          "cv",
          "drop_proba_col",
          "gaussiannb",
          "kneighborsclassifier",
          "meta_classifier",
          "n_jobs",
          "pre_dispatch",
          "random_state",
          "randomforestclassifier",
          "shuffle",
          "store_train_meta_features",
          "stratify",
          "use_clones",
          "use_features_in_secondary",
          "use_probas",
          "verbose",
      ]
      assert got == expect, got
  
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 16 for calling a global function with example usage: test_get_params() without return types