def METHOD_NAME(data_args, parameter_tuning_method):
    """Test if sklearn parameter tuners can handle sktime panel data and classifiers."""
    clf = CanonicalIntervalForest.create_test_instance()
    param_grid = {"n_intervals": [2, 3], "att_subsample_size": [2, 3]}
    fit_args = make_classification_problem(**data_args)
    parameter_tuning_method = parameter_tuning_method(
        clf, param_grid, cv=KFold(n_splits=3)
    )
    parameter_tuning_method.fit(*fit_args)
    assert isinstance(parameter_tuning_method.best_estimator_, CanonicalIntervalForest)