def test_kne_proba(knn_methods):
pool_classifiers, X_dsel, y_dsel, X_test, y_test = setup_classifiers()
kne = KNORAE(pool_classifiers, knn_classifier=knn_methods, voting='soft')
kne.fit(X_dsel, y_dsel)
probas = kne.predict_proba(X_test)
expected = np.load(
'deslib/tests/expected_values/kne_proba_integration.npy')
assert np.allclose(probas, expected)
def test_knorae_subspaces():
rng = np.random.RandomState(123456)
X_dsel, X_test, X_train, y_dsel, y_test, y_train = load_dataset(None, rng)
pool = BaggingClassifier(LogisticRegression(),
max_features=0.5,
random_state=rng).fit(X_train, y_train)
knorae = KNORAE(pool)
knorae.fit(X_dsel, y_dsel)
y_pred = knorae.predict_proba(X_test).argmax(axis=1)
assert np.isclose(accuracy_score(y_pred, y_test), 0.9787234042553191)