def METHOD_NAME(C, gamma, tol, class_weight, joblib_backend="loky"):
    digits = datasets.load_digits()
    X = digits.data
    y = digits.target
    model = SVC(kernel="rbf", C=C, gamma=gamma, tol=tol, class_weight=class_weight)
    # Single metric evaluation using cross_validate
    with joblib.parallel_backend(joblib_backend):
        cv_results = cross_validate(model, X, y, cv=5)
    accuracy = numpy.mean(cv_results["test_score"])
    error_rate = 1 - accuracy
    return [{"name": "test_error_rate", "type": "objective", "value": error_rate}]