def METHOD_NAME(self):
    X = pd.DataFrame(np.random.uniform(low=0.0, high=100, size=(10, 10)))
    y = pd.Series(np.random.uniform(low=0.0, high=100, size=(10,)))
    model = SklearnModel(model='LinearRegression')
    splitter = SklearnDataSplitter(splitter='RepeatedKFold', n_repeats=10, n_splits=5, parallel_run=parallel_run)
    splitter.evaluate(X=X, y=y, models=[model], savepath=os.getcwd(), plots=list())
    for d in splitter.splitdirs:
        self.assertTrue(os.path.exists(d))
        shutil.rmtree(d)
    return