def process_sdml(self, **option): '''Metric Learning algorithm: SDML''' GeneExp = self.GeneExp_train Label = self.Label_train sdml = SDML_Supervised(**option) sdml.fit(GeneExp, Label) self.Trans['SDML'] = sdml.transformer()
def test_sdml_supervised(self): seed = np.random.RandomState(1234) sdml = SDML_Supervised(num_constraints=1500) sdml.fit(self.X, self.y, random_state=seed) L = sdml.transformer() assert_array_almost_equal(L.T.dot(L), sdml.metric())
def test_sdml_supervised(self): seed = np.random.RandomState(1234) sdml = SDML_Supervised(num_constraints=1500) sdml.fit(self.X, self.y, random_state=seed) L = sdml.transformer() assert_array_almost_equal(L.T.dot(L), sdml.metric())