test_bagging.py 文件源码

def test_base_estimator():
    # Check base_estimator and its default values.
    rng = check_random_state(0)

    # Classification
    X_train, X_test, y_train, y_test = train_test_split(iris.data,
                                                        iris.target,
                                                        random_state=rng)

    ensemble = BaggingClassifier(None,
                                 n_jobs=3,
                                 random_state=0).fit(X_train, y_train)

    assert_true(isinstance(ensemble.base_estimator_, DecisionTreeClassifier))

    ensemble = BaggingClassifier(DecisionTreeClassifier(),
                                 n_jobs=3,
                                 random_state=0).fit(X_train, y_train)

    assert_true(isinstance(ensemble.base_estimator_, DecisionTreeClassifier))

    ensemble = BaggingClassifier(Perceptron(),
                                 n_jobs=3,
                                 random_state=0).fit(X_train, y_train)

    assert_true(isinstance(ensemble.base_estimator_, Perceptron))

    # Regression
    X_train, X_test, y_train, y_test = train_test_split(boston.data,
                                                        boston.target,
                                                        random_state=rng)

    ensemble = BaggingRegressor(None,
                                n_jobs=3,
                                random_state=0).fit(X_train, y_train)

    assert_true(isinstance(ensemble.base_estimator_, DecisionTreeRegressor))

    ensemble = BaggingRegressor(DecisionTreeRegressor(),
                                n_jobs=3,
                                random_state=0).fit(X_train, y_train)

    assert_true(isinstance(ensemble.base_estimator_, DecisionTreeRegressor))

    ensemble = BaggingRegressor(SVR(),
                                n_jobs=3,
                                random_state=0).fit(X_train, y_train)
    assert_true(isinstance(ensemble.base_estimator_, SVR))