def test_fit_by_cross_validation(self):
x = EncodedData(
np.array([[1, 0, 0], [0, 1, 1], [1, 1, 1], [0, 1, 1], [1, 0, 0],
[0, 1, 1], [1, 1, 1], [0, 1, 1]]), {
"t1": [1, 0, 2, 0, 1, 0, 2, 0],
"t2": [1, 0, 2, 0, 1, 0, 2, 0]
})
svm = SVC(parameter_grid={"penalty": ["l1"], "dual": [False]})
svm.fit_by_cross_validation(x, number_of_splits=2, label_name="t1")
def test_predict(self):
x = np.array([[1, 0, 0], [0, 1, 1], [1, 1, 1], [0, 1, 1]])
y = {"test": np.array([1, 0, 2, 0])}
svm = SVC()
svm.fit(EncodedData(x, y), "test")
test_x = np.array([[0, 1, 0], [1, 0, 0]])
y = svm.predict(EncodedData(test_x), 'test')["test"]
self.assertTrue(len(y) == 2)
self.assertTrue(y[0] in [0, 1, 2])
self.assertTrue(y[1] in [0, 1, 2])
def test_load(self):
x = np.array([[1, 0, 0], [0, 1, 1], [1, 1, 1], [0, 1, 1]])
y = {"default": np.array([1, 0, 2, 0])}
svm = SVC()
svm.fit(EncodedData(x, y), 'default')
path = EnvironmentSettings.tmp_test_path / "my_svc2/"
PathBuilder.build(path)
with open(path / "svc.pickle", "wb") as file:
pickle.dump(svm.get_model(), file)
svm2 = SVC()
svm2.load(path)
self.assertTrue(isinstance(svm2.get_model(), LinearSVC))
shutil.rmtree(path)
def test_store(self):
x = np.array([[1, 0, 0], [0, 1, 1], [1, 1, 1], [0, 1, 1]])
y = {"default": np.array(['a', "b", "c", "a"])}
svm = SVC()
svm.fit(EncodedData(x, y), 'default')
path = EnvironmentSettings.root_path / "my_svc/"
svm.store(path)
self.assertTrue(os.path.isfile(path / "svc.pickle"))
with open(path / "svc.pickle", "rb") as file:
svm2 = pickle.load(file)
self.assertTrue(isinstance(svm2, LinearSVC))
shutil.rmtree(path)
def test_fit(self):
x = np.array([[1, 0, 0], [0, 1, 1], [1, 1, 1], [0, 1, 1]])
y = {"default": np.array([1, 0, 2, 0])}
svm = SVC()
svm.fit(EncodedData(x, y), 'default')