Python SDML_Supervised.transformer Examples

Example #1

File: algorithms.py Project: RayGit/LINCS

    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()

Example #2

File: test_transformer_metric_conversion.py Project: qjkobe/Papers

 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())

Example #3

File: test_transformer_metric_conversion.py Project: svecon/metric-learn

 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())