code: def test_multilabel_classifier_error(pyplot, response_method):
      """Check that multilabel classifier raises correct error."""
      X, y = make_multilabel_classification(random_state=0)
      X = X[:, :2]
      tree = DecisionTreeClassifier().fit(X, y)
  
      msg = "Multi-label and multi-output multi-class classifiers are not supported"
      with pytest.raises(ValueError, match=msg):
          DecisionBoundaryDisplay.from_estimator(
              tree,
              X,
              response_method=response_method,
          )
  
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 14 for calling a global function with example usage: test_multilabel_classifier_error(pyplot, response_method) without return types