def test_prox_sdca_smooth_hinge_elastic():
clf = ProxSDCA_Classifier(alpha=0.5,
l1_ratio=0.85,
loss="smooth_hinge",
random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(clf.score(X_bin, y_bin), 1.0)
def test_sdca_hinge_multiclass():
clf = ProxSDCA_Classifier(alpha=1e-2,
max_iter=100,
loss="hinge",
random_state=0)
clf.fit(X, y)
assert_almost_equal(clf.score(X, y), 0.947, 3)
def test_prox_sdca_absolute_l1_only():
clf = ProxSDCA_Classifier(alpha=0.5,
l1_ratio=1.0,
loss="absolute",
tol=1e-2,
max_iter=200,
random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(clf.score(X_bin, y_bin), 1.0)
def test_prox_sdca_callback():
class Callback(object):
def __init__(self, X, y):
self.X = X
self.y = y
self.acc = []
def __call__(self, clf):
score = clf.score(self.X, self.y)
self.acc.append(score)
cb = Callback(X_bin, y_bin)
clf = ProxSDCA_Classifier(alpha=0.5, l1_ratio=0.85, loss="hinge",
callback=cb, random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(cb.acc[0], 0.5)
assert_equal(cb.acc[-1], 1.0)
def test_prox_sdca_callback():
class Callback(object):
def __init__(self, X, y):
self.X = X
self.y = y
self.acc = []
def __call__(self, clf):
score = clf.score(self.X, self.y)
self.acc.append(score)
cb = Callback(X_bin, y_bin)
clf = ProxSDCA_Classifier(alpha=0.5,
l1_ratio=0.85,
loss="hinge",
callback=cb,
random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(cb.acc[0], 0.5)
assert_equal(cb.acc[-1], 1.0)
def test_prox_sdca_absolute_l1_only():
clf = ProxSDCA_Classifier(alpha=0.5, l1_ratio=1.0, loss="absolute",
tol=1e-2, max_iter=200, random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(clf.score(X_bin, y_bin), 1.0)
def test_prox_sdca_smooth_hinge_elastic():
clf = ProxSDCA_Classifier(alpha=0.5, l1_ratio=0.85, loss="smooth_hinge",
random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(clf.score(X_bin, y_bin), 1.0)
def test_sdca_absolute():
clf = ProxSDCA_Classifier(loss="absolute", random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(clf.score(X_bin, y_bin), 1.0)
def test_sdca_squared():
clf = ProxSDCA_Classifier(loss="squared", random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(clf.score(X_bin, y_bin), 1.0)
def test_sdca_hinge_multiclass():
clf = ProxSDCA_Classifier(alpha=1e-2, max_iter=100, loss="hinge",
random_state=0)
clf.fit(X, y)
assert_almost_equal(clf.score(X, y), 0.947, 3)
def test_sdca_absolute():
clf = ProxSDCA_Classifier(loss="absolute", random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(clf.score(X_bin, y_bin), 1.0)
def test_sdca_squared():
clf = ProxSDCA_Classifier(loss="squared", random_state=0)
clf.fit(X_bin, y_bin)
assert_equal(clf.score(X_bin, y_bin), 1.0)