code: def test_boss_ensemble_classes(dataset, new_class, expected_dtype):
      """Test BOSS Ensemble on unit_test data with different datatypes as classes."""
      # load unit test data
      X_train, y_train, X_test, y_test = dataset
  
      # change class
      y_train = np.array([new_class[y] for y in y_train])
  
      # train boss_ensemble and predict X_test
      boss_ensemble = BOSSEnsemble()
      boss_ensemble.fit(X_train, y_train)
      y_pred = boss_ensemble.predict(X_test)
  
      # assert class type and names
      assert y_pred.dtype == expected_dtype
      assert set(y_pred) == set(y_train)
  
imports: import numpy
  import pytest
  from sktime.classification.dictionary_based import BOSSEnsemble, IndividualBOSS
  from sktime.datasets import load_unit_test
  from sktime.tests.test_switch import run_test_for_class
label_desc: Use image node_id 3 for calling a global function with example usage: test_boss_ensemble_classes(dataset, new_class, expected_dtype) without return types