人工神经网络及应用答案2023秋

第十二章测试

1.The loss function of AdaBoost algorithm is（ ）.
A:exponential function
B:nonlinear function C:linear function
D:logarithmic function
答案:A
2.Boosting algorithm is the general name of a class of algorithms. Their common ground is to construct a strong classifier by using a group of weak classifiers. Weak classifier mainly refers to the classifier whose prediction accuracy is not high and far below the ideal classification effect. Strong classifier mainly refers to the classifier with high prediction accuracy. （ ）
A:错 B:对 3.Among the many improved boosting algorithms, the most successful one is the AdaBoost (adaptive boosting) algorithm proposed by Yoav Freund of University of California San Diego and Robert Schapire of Princeton University in 1996. （ ）
A:错 B:对 4.The most basic property of AdaBoost is that it reduces the training error continuously in the learning process, that is, the classification error rate on the training data set until each weak classifier is combined into the final ideal classifier. （ ）
A:错 B:对 5.The main purpose of adding regularization term into the formula of calculating strong classifier is to prevent the over fitting of AdaBoost algorithm, which is usually called step size in algorithm. （ ）
A:错 B:对