test_bagging.py 文件源码

def test_warm_start_equivalence():
    # warm started classifier with 5+5 estimators should be equivalent to
    # one classifier with 10 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_ws = BaggingClassifier(n_estimators=5, warm_start=True,
                               random_state=3141)
    clf_ws.fit(X_train, y_train)
    clf_ws.set_params(n_estimators=10)
    clf_ws.fit(X_train, y_train)
    y1 = clf_ws.predict(X_test)

    clf = BaggingClassifier(n_estimators=10, warm_start=False,
                            random_state=3141)
    clf.fit(X_train, y_train)
    y2 = clf.predict(X_test)

    assert_array_almost_equal(y1, y2)