def METHOD_NAME(pipeline_name, name, path):
    if pipeline_name == "LR":
        pipeline = make_pipeline(LogisticRegression())
    if pipeline_name == "FGS":
        pipeline = make_pipeline(FeatureGradientSelector(), LogisticRegression())
    if pipeline_name == "Tree":
        pipeline = make_pipeline(SelectFromModel(ExtraTreesClassifier(n_estimators=50)), LogisticRegression())
    test_benchmark = Benchmark()
    print("Dataset:\t", name)
    print("Pipeline:\t", pipeline_name)
    starttime = datetime.datetime.now()
    test_benchmark.run_test(pipeline, name, path)
    endtime = datetime.datetime.now()
    print("Used time: ", (endtime - starttime).microseconds/1000)
    print("")