def test_istrained_with_load(self): old_backend = Backend() dataset = datasets.load_iris() old_backend.load(dataset) old_backend.fit() new_backend = Backend() self.assertTrue(new_backend.istrained(read=True))
def test_predict_when_trained(self): backend = Backend() dataset = datasets.load_iris() backend.load(dataset) backend.fit() sample = dataset["data"][:10] predictions = backend.predict(sample) self.assertEqual(len(predictions), 10)
def test_istrained_without_load(self): backend = Backend() dataset = datasets.load_iris() self.assertFalse(backend.istrained()) backend.load(dataset) self.assertFalse(backend.istrained()) backend.fit() self.assertTrue(backend.istrained())
def test_fit_when_loaded(self): backend = Backend() dataset = datasets.load_iris() backend.load(dataset) self.assertTrue(backend.fit())
def test_fit_when_not_loaded(self): backend = Backend() with self.assertRaises(RuntimeError): backend.fit()