def test_BasisfunctionRegression_simple(): x = np.arange(10.).reshape((10, 1)) y = np.arange(10.) + 1 dy = 1 mu = np.arange(11.)[:, None] sigma = 1.0 clf = BasisFunctionRegression(mu=mu, sigma=sigma).fit(x, y, dy) y_true = clf.predict(x) assert_allclose(y, y_true, atol=1E-10)
def fit_BasisFunction(features_train, labels_train, features_pred, kernel='gaussian', mu=mu0, sigma=0.1): model = BasisFunctionRegression(kernel, mu=mu, sigma=sigma) model.fit(features_train, labels_train) labels_pred = model.predict(features_pred) return labels_pred