code: def test_stacking_classifier(final_estimator):
      estimators = [
          ("mlp", MLPClassifier(alpha=0.001)),
          ("tree", DecisionTreeClassifier()),
      ]
      clf = StackingClassifier(
          estimators=estimators, final_estimator=final_estimator
      )
  
      html_output = estimator_html_repr(clf)
  
      assert html.escape(str(clf)) in html_output
      # If final_estimator's default changes from LogisticRegression
      # this should be updated
      if final_estimator is None:
          assert "LogisticRegression(" in html_output
      else:
          assert final_estimator.__class__.__name__ in html_output
  
imports: import html
  import locale
  import re
  from contextlib import closing
  from io import StringIO
  from unittest.mock import patch
  import pytest
  from sklearn import config_context
  from sklearn.base import BaseEstimator
  from sklearn.cluster import AgglomerativeClustering, Birch
  from sklearn.compose import ColumnTransformer, make_column_transformer
  from sklearn.datasets import load_iris
  from sklearn.decomposition import PCA, TruncatedSVD
  from sklearn.ensemble import StackingClassifier, StackingRegressor, VotingClassifier
  from sklearn.feature_selection import SelectPercentile
  from sklearn.gaussian_process.kernels import ExpSineSquared
  from sklearn.impute import SimpleImputer
  from sklearn.kernel_ridge import KernelRidge
  from sklearn.linear_model import LogisticRegression
  from sklearn.model_selection import RandomizedSearchCV
  from sklearn.multiclass import OneVsOneClassifier
  from sklearn.neural_network import MLPClassifier
  from sklearn.pipeline import FeatureUnion, Pipeline, make_pipeline
  from sklearn.preprocessing import OneHotEncoder, StandardScaler
  from sklearn.svm import LinearSVC, LinearSVR
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.utils._estimator_html_repr import _get_css_style, _get_visual_block, _HTMLDocumentationLinkMixin, _write_label_html, estimator_html_repr
  from sklearn.utils.fixes import parse_version
label_desc: Use image node_id 9 for calling a global function with example usage: test_stacking_classifier(final_estimator) without return types