code: def test_stacking_classifier_drop_column_binary_classification():
      # check that a column is dropped in binary classification
      X, y = load_breast_cancer(return_X_y=True)
      X_train, X_test, y_train, _ = train_test_split(
          scale(X), y, stratify=y, random_state=42
      )
  
      # both classifiers implement 'predict_proba' and will both drop one column
      estimators = [
          ("lr", LogisticRegression()),
          ("rf", RandomForestClassifier(random_state=42)),
      ]
      clf = StackingClassifier(estimators=estimators, cv=3)
  
      clf.fit(X_train, y_train)
      X_trans = clf.transform(X_test)
      assert X_trans.shape[1] == 2
  
      # LinearSVC does not implement 'predict_proba' and will not drop one column
      estimators = [
          ("lr", LogisticRegression()),
          ("svc", LinearSVC(dual="auto")),
      ]
      clf.set_params(estimators=estimators)
  
      clf.fit(X_train, y_train)
      X_trans = clf.transform(X_test)
      assert X_trans.shape[1] == 2
  
imports: from unittest.mock import Mock
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from scipy import sparse
  from sklearn.base import BaseEstimator, ClassifierMixin, RegressorMixin, clone
  from sklearn.datasets import load_breast_cancer, load_diabetes, load_iris, make_classification, make_multilabel_classification, make_regression
  from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor, StackingClassifier, StackingRegressor
  from sklearn.exceptions import ConvergenceWarning, NotFittedError
  from sklearn.linear_model import LinearRegression, LogisticRegression, Ridge, RidgeClassifier
  from sklearn.model_selection import KFold, StratifiedKFold, train_test_split
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.neural_network import MLPClassifier
  from sklearn.preprocessing import scale
  from sklearn.svm import SVC, LinearSVC, LinearSVR
  from sklearn.utils._mocking import CheckingClassifier
  from sklearn.utils._testing import assert_allclose, assert_allclose_dense_sparse, ignore_warnings
  from sklearn.utils.fixes import COO_CONTAINERS, CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 2 for calling a global function with example usage: test_stacking_classifier_drop_column_binary_classification() without return types