def test_multiclass_hinge_sgd():
for data in (mult_dense, mult_csr):
for fit_intercept in (True, False):
clf = SGDClassifier(loss="hinge", multiclass=True,
fit_intercept=fit_intercept, random_state=0)
clf.fit(data, mult_target)
assert_greater(clf.score(data, mult_target), 0.78)
def test_multiclass_hinge_sgd_l1l2():
for data in (mult_dense, mult_csr):
clf = SGDClassifier(loss="hinge",
penalty="l1/l2",
multiclass=True,
random_state=0)
clf.fit(data, mult_target)
assert_greater(clf.score(data, mult_target), 0.75)
def test_multiclass_hinge_sgd_l1l2(data, request):
X, y = request.getfixturevalue(data)
clf = SGDClassifier(loss="hinge",
penalty="l1/l2",
multiclass=True,
random_state=0)
clf.fit(X, y)
assert clf.score(X, y) > 0.75
def test_multiclass_hinge_sgd(data, fit_intercept, request):
X, y = request.getfixturevalue(data)
clf = SGDClassifier(loss="hinge",
multiclass=True,
fit_intercept=fit_intercept,
random_state=0)
clf.fit(X, y)
assert clf.score(X, y) > 0.78
def test_multiclass_squared_hinge_sgd():
for data in (mult_dense, mult_csr):
for fit_intercept in (True, False):
clf = SGDClassifier(loss="squared_hinge", multiclass=True,
learning_rate="constant", eta0=1e-3,
fit_intercept=fit_intercept, random_state=0)
clf.fit(data, mult_target)
assert_greater(clf.score(data, mult_target), 0.78)
def test_multiclass_squared_hinge_sgd(data, fit_intercept, request):
X, y = request.getfixturevalue(data)
clf = SGDClassifier(loss="squared_hinge",
multiclass=True,
learning_rate="constant",
eta0=1e-3,
fit_intercept=fit_intercept,
random_state=0)
clf.fit(X, y)
assert clf.score(X, y) > 0.78
def test_multiclass_sgd():
clf = SGDClassifier(random_state=0)
clf.fit(mult_dense, mult_target)
assert_greater(clf.score(mult_dense, mult_target), 0.80)
assert_equal(list(clf.classes_), [0, 1, 2])
def test_multiclass_hinge_sgd_l1l2():
for data in (mult_dense, mult_csr):
clf = SGDClassifier(loss="hinge", penalty="l1/l2", multiclass=True, random_state=0)
clf.fit(data, mult_target)
assert_greater(clf.score(data, mult_target), 0.75)
def test_multiclass_sgd():
clf = SGDClassifier(random_state=0)
clf.fit(mult_dense, mult_target)
assert_greater(clf.score(mult_dense, mult_target), 0.80)
def test_multiclass_sgd():
clf = SGDClassifier(random_state=0)
clf.fit(mult_dense, mult_target)
assert_greater(clf.score(mult_dense, mult_target), 0.80)
def test_multiclass_sgd():
clf = SGDClassifier(random_state=0)
clf.fit(mult_dense, mult_target)
assert clf.score(mult_dense, mult_target) > 0.80
assert list(clf.classes_) == [0, 1, 2]
def test_multiclass_sgd():
clf = SGDClassifier(random_state=0)
clf.fit(mult_dense, mult_target)
assert_greater(clf.score(mult_dense, mult_target), 0.80)
assert_equal(list(clf.classes_), [0, 1, 2])