def METHOD_NAME(self):
    # Make entries at a 10% spacing
    composition_df = pd.DataFrame({'composition': ['Al{}Cu{}'.format(i, 10-i) for i in range(11)]})
    X = pd.DataFrame(np.random.uniform(low=0.0, high=100, size=(11, 10)))
    y = pd.Series(np.random.uniform(low=0.0, high=100, size=(11,)))
    # Generate test splits with a 5% distance cutoff
    splitter = LeaveCloseCompositionsOut(composition_df=composition_df, dist_threshold=0.5, parallel_run=parallel_run)
    model = SklearnModel(model='LinearRegression')
    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