test_uncorrelated_mo_rf_with_instances.py 文件源码

def test_train_and_predict_with_rf(self):
        rs = np.random.RandomState(1)
        X = rs.rand(20, 10)
        Y = rs.rand(10, 2)
        model = UncorrelatedMultiObjectiveRandomForestWithInstances(
            ['cost', 'ln(runtime)'],
            types=np.zeros((10, ), dtype=np.uint),
            bounds=np.array([
                (0, np.nan), (0, np.nan), (0, np.nan), (0, np.nan), (0, np.nan),
                (0, np.nan), (0, np.nan), (0, np.nan), (0, np.nan), (0, np.nan)
            ], dtype=object),
            rf_kwargs={'seed': 1},
            pca_components=5
        )
        self.assertEqual(model.estimators[0].seed, 1)
        self.assertEqual(model.estimators[1].seed, 1)
        self.assertEqual(model.pca_components, 5)
        model.train(X[:10], Y)
        m, v = model.predict(X[10:])
        self.assertEqual(m.shape, (10, 2))
        self.assertEqual(v.shape, (10, 2))