code: def test_check_boundary_response_method_error():
      """Check that we raise an error for the cases not supported by
      `_check_boundary_response_method`.
      """
  
      class MultiLabelClassifier:
          classes_ = [np.array([0, 1]), np.array([0, 1])]
  
      err_msg = "Multi-label and multi-output multi-class classifiers are not supported"
      with pytest.raises(ValueError, match=err_msg):
          _check_boundary_response_method(
              MultiLabelClassifier(), "predict", None
          )
  
      class MulticlassClassifier:
          classes_ = [0, 1, 2]
  
      err_msg = "Multiclass classifiers are only supported when `response_method` is"
      for response_method in ("predict_proba", "decision_function"):
          with pytest.raises(ValueError, match=err_msg):
              _check_boundary_response_method(
                  MulticlassClassifier(), response_method, None
              )
  
imports: import warnings
  import numpy
  import pytest
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.datasets import load_diabetes, load_iris, make_classification, make_multilabel_classification
  from sklearn.ensemble import IsolationForest
  from sklearn.inspection import DecisionBoundaryDisplay
  from sklearn.inspection._plot.decision_boundary import _check_boundary_response_method
  from sklearn.linear_model import LogisticRegression
  from sklearn.preprocessing import scale
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from sklearn.utils._testing import assert_allclose, assert_array_equal
label_desc: Use image node_id 4 for calling a global function with example usage: test_check_boundary_response_method_error() without return types