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It is easy to see that OvR only needs to train N classifiers, while OvO needs to train N (N-1)/2 classifiers, so the storage overhead and test time overhead of OvO are usually larger than OvR. However, in training, each classifier of OVR uses all training samples, while each classifier of OVO only uses samples of two classes. Therefore, when there are many classes, the training time cost of OVO is usually smaller than that of OVR. As for the prediction performance, it depends on the specific data distribution, which is similar in most cases.InitialValue whose value is used for the first parameter of the first call to callbackThe protagonists of the three stories, I have hidden their names in order to protect them. However, I wrote them into the story to protect our border with news. On Xinjiang's 5,600-kilometer border, there are also border guards from Tajik, Kazak, Uygur, Han and other ethnic groups, all telling the same story.凯瑟琳自杀后，约翰·卡迪纳警探表面上接受了她自杀的证据，但当他开始收到嘲笑她的贺卡，指责他是她自杀的罪魁祸首时，他开始质疑自杀。Xinhua News Agency International Department Ling Shuo