test_logitboost.py 文件源码

def test_logitboost_hastie_fitting():
    c = LogitBoostClassifier(
            base_estimator=DecisionTreeRegressor(max_depth=1),
            n_estimators=30,
            learning_rate=1.0
    )
    data = Hastie_10_2()
    c.fit(data.data, np.sign(data.labels))
    assert_array_less(c.estimator_errors_, 0.5)
    assert zero_one_loss(np.sign(data.labels), c.predict(data.data)) < 0.2