10.2 adaboost regression.py 文件源码

def test_AdaBoostRegressor_loss(*data):
    '''
    test the method with different loss function
    :param data:    train_data, test_data, train_value, test_value
    :return: None
    '''
    X_train,X_test,y_train,y_test=data
    losses=['linear','square','exponential']
    fig=plt.figure()
    ax=fig.add_subplot(1,1,1)
    for i ,loss in enumerate(losses):
        regr=ensemble.AdaBoostRegressor(loss=loss,n_estimators=30)
        regr.fit(X_train,y_train)
        ## graph
        estimators_num=len(regr.estimators_)
        X=range(1,estimators_num+1)
        ax.plot(list(X),list(regr.staged_score(X_train,y_train)),
            label="Traing score:loss=%s"%loss)
        ax.plot(list(X),list(regr.staged_score(X_test,y_test)),
            label="Testing score:loss=%s"%loss)
        ax.set_xlabel("estimator num")
        ax.set_ylabel("score")
        ax.legend(loc="lower right")
        ax.set_ylim(-1,1)
    plt.suptitle("AdaBoostRegressor")
    plt.show()