test_bagging.py 文件源码

def test_warm_start_equal_n_estimators():
    # Test that nothing happens when fitting without increasing n_estimators
    X, y = make_hastie_10_2(n_samples=20, random_state=1)
    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=43)

    clf = BaggingClassifier(n_estimators=5, warm_start=True, random_state=83)
    clf.fit(X_train, y_train)

    y_pred = clf.predict(X_test)
    # modify X to nonsense values, this should not change anything
    X_train += 1.

    assert_warns_message(UserWarning,
                         "Warm-start fitting without increasing n_estimators does not",
                         clf.fit, X_train, y_train)
    assert_array_equal(y_pred, clf.predict(X_test))