def test_decision_function(self, data):
classes = np.array([-1., 1.])
raw_model = VW(loss_function='logistic')
raw_model.fit(data.x, data.y)
predictions = raw_model.predict(data.x)
class_indices = (predictions > 0).astype(np.int)
class_predictions = classes[class_indices]
model = VWClassifier()
model.fit(data.x, data.y)
assert np.allclose(class_predictions, model.predict(data.x))
def test_predict_proba(self, data):
model = VWClassifier()
model.fit(data.x, data.y)
actual = model.predict_proba(data.x)
assert actual.shape[0] == 100
assert np.allclose(actual[0], [0.3997, 0.6003], atol=1e-4)
def test_decision_function(self, data):
model = VWClassifier()
model.fit(data.x, data.y)
actual = model.decision_function(data.x)
assert actual.shape[0] == 100
assert np.isclose(actual[0], 0.4069, atol=1e-4)