code: def test_transform_stacking_classifier():
      """Test transform method of StackingClassifier class."""
      df_train = pd.read_csv("data_for_tests/clean_train.csv")
      y_train = pd.read_csv(
          "data_for_tests/clean_target.csv", squeeze=True
      )
      df_test = pd.read_csv("data_for_tests/clean_test.csv")
      stacking_classifier = StackingClassifier()
      with pytest.raises(ValueError):
          stacking_classifier.transform(None)
      with pytest.raises(ValueError):
          stacking_classifier.transform(df_test)
      stacking_classifier.fit_transform(df_train, y_train)
      results = stacking_classifier.transform(df_test)
      assert len(results.columns == 3)
  
file_path: MLBox/tests/test_stacking_classifer.py
imports: import pytest
  import pandas
  import numpy
  from sklearn.linear_model import LogisticRegression
  from mlbox.model.classification.stacking_classifier import StackingClassifier
label_desc: Use image node_id 5 for calling a global function with example usage: test_transform_stacking_classifier() without return types