code: def test_support_missing_values(MultiClassClassifier):
      # smoke test to check that pipeline OvR and OvO classifiers are letting
      # the validation of missing values to
      # the underlying pipeline or classifiers
      rng = np.random.RandomState(42)
      X, y = iris.data, iris.target
      X = np.copy(X)  # Copy to avoid that the original data is modified
      mask = rng.choice([1, 0], X.shape, p=[0.1, 0.9]).astype(bool)
      X[mask] = np.nan
      lr = make_pipeline(
          SimpleImputer(), LogisticRegression(random_state=rng)
      )
  
      MultiClassClassifier(lr).fit(X, y).score(X, y)
  
imports: from re import escape
  import numpy
  import pytest
  import scipy.sparse
  from numpy.testing import assert_allclose
  from sklearn import datasets, svm
  from sklearn.datasets import load_breast_cancer
  from sklearn.exceptions import NotFittedError
  from sklearn.impute import SimpleImputer
  from sklearn.linear_model import ElasticNet, Lasso, LinearRegression, LogisticRegression, Perceptron, Ridge, SGDClassifier
  from sklearn.metrics import precision_score, recall_score
  from sklearn.model_selection import GridSearchCV, cross_val_score
  from sklearn.multiclass import OneVsOneClassifier, OneVsRestClassifier, OutputCodeClassifier
  from sklearn.naive_bayes import MultinomialNB
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.pipeline import Pipeline, make_pipeline
  from sklearn.svm import SVC, LinearSVC
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from sklearn.utils import check_array, shuffle
  from sklearn.utils._mocking import CheckingClassifier
  from sklearn.utils._testing import assert_almost_equal, assert_array_equal
  from sklearn.utils.fixes import COO_CONTAINERS, CSC_CONTAINERS, CSR_CONTAINERS, DOK_CONTAINERS, LIL_CONTAINERS
  from sklearn.utils.multiclass import check_classification_targets, type_of_target
label_desc: Use image node_id 40 for calling a global function with example usage: test_support_missing_values(MultiClassClassifier) without return types