def test_mds_params(self):
np.random.seed(14)
X = np.random.random((10, 2))
y = np.random.randint(0, 2, 10)
X_cand = np.random.random((15, 2))
alce = ALCE(self.classes,
self.regressor,
self.cost_matrix,
random_state=14,
mds_params={
'n_jobs': 1,
'verbose': 2
})
cand1 = alce.query(X_cand, X, y)
alce = ALCE(self.classes,
self.regressor,
self.cost_matrix,
random_state=14,
mds_params={'n_jobs': 2})
cand2 = alce.query(X_cand, X, y)
np.testing.assert_array_equal(cand1, cand2)
alce = ALCE(self.classes,
self.regressor,
self.cost_matrix,
mds_params={'dissimilarity': 'wrong'})
self.assertRaises(ValueError, alce.query, X_cand, X, y)
alce = ALCE(base_regressor=self.regressor,
classes=[0, 1],
mds_params={'dissimilarity': 'precomputed'})
query_indices = alce.query([[0], [100], [200]], [[0], [200]], [0, 1])
np.testing.assert_array_equal(query_indices, [1])
def test_query_param_X(self):
alce = ALCE(self.classes, self.regressor, self.cost_matrix)
self.assertRaises(ValueError,
alce.query,
X_cand=self.X_cand,
X=np.ones((5, 3)),
y=self.y)
_, result = alce.query(self.X_cand,
X=self.X,
y=[MISSING_LABEL] * len(self.X),
return_utilities=True)
np.testing.assert_array_equal(result, np.ones((1, len(self.X_cand))))
def test_query(self):
alce = ALCE(base_regressor=self.regressor, classes=[0, 1])
query_indices = alce.query([[0], [100], [200]], [[0], [200]], [0, 1])
np.testing.assert_array_equal(query_indices, [1])