test_weight_boosting.py 文件源码

def test_gridsearch():
    # Check that base trees can be grid-searched.
    # AdaBoost classification
    boost = AdaBoostClassifier(base_estimator=DecisionTreeClassifier())
    parameters = {'n_estimators': (1, 2),
                  'base_estimator__max_depth': (1, 2),
                  'algorithm': ('SAMME', 'SAMME.R')}
    clf = GridSearchCV(boost, parameters)
    clf.fit(iris.data, iris.target)

    # AdaBoost regression
    boost = AdaBoostRegressor(base_estimator=DecisionTreeRegressor(),
                              random_state=0)
    parameters = {'n_estimators': (1, 2),
                  'base_estimator__max_depth': (1, 2)}
    clf = GridSearchCV(boost, parameters)
    clf.fit(boston.data, boston.target)