def test_weasel_on_gunpoint():
# load gunpoint data
X_train, y_train = load_gunpoint(split="train", return_X_y=True)
X_test, y_test = load_gunpoint(split="test", return_X_y=True)
# train WEASEL
weasel = WEASEL(random_state=1, binning_strategy="equi-depth")
weasel.fit(X_train, y_train)
score = weasel.score(X_test, y_test)
# print(score)
assert score >= 0.99
def test_weasel_on_power_demand():
# load power demand data
X_train, y_train = load_italy_power_demand(split="train", return_X_y=True)
X_test, y_test = load_italy_power_demand(split="test", return_X_y=True)
# train WEASEL
weasel = WEASEL(random_state=1, binning_strategy="kmeans")
weasel.fit(X_train, y_train)
score = weasel.score(X_test, y_test)
# print(score)
assert score >= 0.94
def test_weasel_on_power_demand():
# load power demand data
X_train, y_train = load_italy_power_demand(split='train', return_X_y=True)
X_test, y_test = load_italy_power_demand(split='test', return_X_y=True)
# train WEASEL
weasel = WEASEL(random_state=47)
weasel.fit(X_train, y_train)
score = weasel.score(X_test, y_test)
print(score)
assert (score >= 0.94)
def test_weasel_on_gunpoint():
# load gunpoint data
X_train, y_train = load_gunpoint(split="train", return_X_y=True)
X_test, y_test = load_gunpoint(split="test", return_X_y=True)
# indices = np.random.RandomState(0).permutation(10)
# train WEASEL
weasel = WEASEL(random_state=1379)
weasel.fit(X_train, y_train)
score = weasel.score(X_test, y_test)
# print(score)
assert score >= 0.99
def test_weasel_on_unit_test_data():
"""Test of WEASEL on unit test data."""
# load unit test data
X_train, y_train = load_unit_test(split="train", return_X_y=True)
X_test, y_test = load_unit_test(split="test", return_X_y=True)
indices = np.random.RandomState(0).choice(len(y_train), 10, replace=False)
# train WEASEL
weasel = WEASEL(random_state=0, window_inc=4)
weasel.fit(X_train, y_train)
# assert probabilities are the same
probas = weasel.predict_proba(X_test.iloc[indices])
testing.assert_array_almost_equal(probas,
weasel_unit_test_probas,
decimal=2)