Python SDML_Supervised.get_mahalanobis_matrix Beispiele

Beispiel #1

Datei: test_components_metric_conversion.py Projekt: zxhou/metric-learn

 def test_sdml_supervised(self):
   seed = np.random.RandomState(1234)
   sdml = SDML_Supervised(num_constraints=1500, prior='identity',
                          balance_param=1e-5, random_state=seed)
   sdml.fit(self.X, self.y)
   L = sdml.components_
   assert_array_almost_equal(L.T.dot(L), sdml.get_mahalanobis_matrix())

Beispiel #2

 def test_sdml_supervised(self):
   seed = np.random.RandomState(1234)
   sdml = SDML_Supervised(num_constraints=1500, use_cov=False,
                          balance_param=1e-5)
   sdml.fit(self.X, self.y, random_state=seed)
   L = sdml.transformer_
   assert_array_almost_equal(L.T.dot(L), sdml.get_mahalanobis_matrix())