Exemplo n.º 1
0
def test_multinomial_checker_cutting_plane():
    X, Y = toy.generate_checker_multinomial(n_samples=10, noise=.1)
    n_labels = len(np.unique(Y))
    crf = GridCRF(n_states=n_labels)
    clf = NSlackSSVM(model=crf, max_iter=20, C=100000, check_constraints=True)
    clf.fit(X, Y)
    Y_pred = clf.predict(X)
    assert_array_equal(Y, Y_pred)
Exemplo n.º 2
0
def test_multinomial_checker_subgradient():
    X, Y = toy.generate_checker_multinomial(n_samples=10, noise=0.0)
    n_labels = len(np.unique(Y))
    crf = GridCRF(n_states=n_labels)
    clf = SubgradientStructuredSVM(problem=crf, max_iter=50, C=10, verbose=0,
                                   momentum=.98, learning_rate=0.01, n_jobs=-1)
    clf.fit(X, Y)
    Y_pred = clf.predict(X)
    assert_array_equal(Y, Y_pred)
Exemplo n.º 3
0
def test_multinomial_checker_cutting_plane():
    X, Y = toy.generate_checker_multinomial(n_samples=10, noise=.1)
    n_labels = len(np.unique(Y))
    crf = GridCRF(n_states=n_labels)
    clf = StructuredSVM(problem=crf, max_iter=20, C=100000, verbose=0,
                        check_constraints=True, n_jobs=-1)
    clf.fit(X, Y)
    Y_pred = clf.predict(X)
    assert_array_equal(Y, Y_pred)