def test_fit_vs_sk_iris(self):
X = load_iris().data
model = KMeans(n_gpus=1, n_clusters=4, random_state=1234).fit(X)
h2o_labels = model.predict(X)
sk_lables = model.sklearn_predict(X)
assert all(h2o_labels == sk_lables)
def test_transform_iris(self):
X = load_iris().data
model = KMeans(n_gpus=1, n_clusters=4, random_state=1234567).fit(X)
labels_from_trans = list(
map(lambda x: np.argmin(x), model.transform(X)))
assert all(labels_from_trans == model.predict(X))
def test_fit_vs_sk_iris(self):
X = load_iris().data
model = KMeans(n_gpus=1, n_clusters=4, random_state=1234).fit(X)
h2o_labels = model.predict(X)
sk_lables = model.sklearn_predict(X)
assert all(h2o_labels == sk_lables)
def test_transform_iris(self):
X = load_iris().data
model = KMeans(n_gpus=1, n_clusters=4, random_state=1234567).fit(X)
labels_from_trans = list(
map(lambda x: np.argmin(x), model.transform(X))
)
assert all(labels_from_trans == model.predict(X))
def test_predict_iris(self):
X = load_iris().data
model = KMeans(n_gpus=1, n_clusters=4, random_state=123456).fit(X)
assert all(model.labels_ == model.predict(X))
def test_predict_iris(self):
X = load_iris().data
model = KMeans(n_gpus=1, n_clusters=4, random_state=123456).fit(X)
assert all(model.labels_ == model.predict(X))
def test_predict_iris(self, order):
X = np.asanyarray(load_iris().data, order=order)
model = KMeans(n_gpus=1, n_clusters=4, random_state=123456).fit(X)
assert all(model.labels_ == model.predict(X))