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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.Blue: bluegrass*, Chinese ixora fruit …这孙鬼是孙铁的远亲，孙铁忍无可忍，踏前一步，对板栗道：少爷，不能饶了这混账。Dogs go and do singing and stuff. EMPOWERING.同住在一座大楼里的五个青年男女，尽管他们的公寓面对面，但他们彼此之间却并不相识，每个人不同的生活习惯和生活方式，使他们或宅在家里，过着足不出户的网络生活；或苦心经营自己的小事业，为能过上更好的生活而奔波。终于有一天，一次在微博上的“找猫”事件，让三个快乐的单身汉与两个彪悍的现代女青年相遇了，他们带着年轻人独有的热忱和发达的信息库圆满的破获了这宗“宠物失踪案”。从此，两幢公寓，男左女右，此时此刻，正上演着一幕幕让人忍俊不禁的囧事，尴尬事、无厘头的荒唐事，而每一件事都能折射出当下年轻人最IN的生活方式。/smirk (smirk)