Code Duplication - SimonBlanke/Optimization-Metadata - Measure and Improve Code Quality continuously with Scrutinizer

Code Duplication Length = 18-18 lines in 2 locations

tests/_test_hyperactive.py 2 locations


    opt.search(search_config)


def test_long_term_memory_without_data():
    def model3(para, X_train, y_train):
        model = DecisionTreeClassifier(
            criterion=para["criterion"], max_depth=para["max_depth"]
        )
        scores = cross_val_score(model, X_train, y_train, cv=2)

        return scores.mean()

    search_config = {
        model3: {"criterion": ["gini", "entropy"], "max_depth": range(1, 11)}
    }

    opt = Hyperactive(X, y, memory="long")
    opt.search(search_config, n_iter=0)

    opt = Hyperactive(X, y, memory="long")
    opt.search(search_config)


def test_long_term_memory_best_model():

    assert diff_time_0 / 2 > diff_time_1


def test_long_term_memory_with_data():
    def model2(para, X_train, y_train):
        model = DecisionTreeClassifier(
            criterion=para["criterion"], max_depth=para["max_depth"]
        )
        scores = cross_val_score(model, X_train, y_train, cv=2)

        return scores.mean()

    search_config = {
        model2: {"criterion": ["gini", "entropy"], "max_depth": range(1, 11)}
    }

    opt = Hyperactive(X, y, memory="long")
    opt.search(search_config)

    opt = Hyperactive(X, y, memory="long")
    opt.search(search_config)


def test_long_term_memory_without_data():

		@@ 62-79 (lines=18) @@
59		opt.search(search_config)
60
61
62		def test_long_term_memory_without_data():
63		def model3(para, X_train, y_train):
64		model = DecisionTreeClassifier(
65		criterion=para["criterion"], max_depth=para["max_depth"]
66		)
67		scores = cross_val_score(model, X_train, y_train, cv=2)
68
69		return scores.mean()
70
71		search_config = {
72		model3: {"criterion": ["gini", "entropy"], "max_depth": range(1, 11)}
73		}
74
75		opt = Hyperactive(X, y, memory="long")
76		opt.search(search_config, n_iter=0)
77
78		opt = Hyperactive(X, y, memory="long")
79		opt.search(search_config)
80
81
82		def test_long_term_memory_best_model():
		@@ 42-59 (lines=18) @@
39		assert diff_time_0 / 2 > diff_time_1
40
41
42		def test_long_term_memory_with_data():
43		def model2(para, X_train, y_train):
44		model = DecisionTreeClassifier(
45		criterion=para["criterion"], max_depth=para["max_depth"]
46		)
47		scores = cross_val_score(model, X_train, y_train, cv=2)
48
49		return scores.mean()
50
51		search_config = {
52		model2: {"criterion": ["gini", "entropy"], "max_depth": range(1, 11)}
53		}
54
55		opt = Hyperactive(X, y, memory="long")
56		opt.search(search_config)
57
58		opt = Hyperactive(X, y, memory="long")
59		opt.search(search_config)
60
61
62		def test_long_term_memory_without_data():

SimonBlanke / Optimization-Metadata

Code Duplication Length = 18-18 lines in 2 locations

tests/_test_hyperactive.py 2 locations