何霆猛一瞪眼道：如何不敢当？这次大战，我军斩杀敌人将领七名，杀敌两万，然我们自己也损兵折将，战果只能算寻常。
The business has been done. When it comes to collecting money, many people will think that I am so familiar with purchasing that I feel embarrassed to chase after his money all day long. Therefore, we seldom chase after the money or don't chase after it several times. In fact, we also have to get the payment for the goods before we can get the commission. It is only natural that we owe him too much, and your business will not last long. I usually ask him to arrange the payment, not to ask him to arrange it, but to say * * Mr., you arrange the payment for the goods for me on Wednesday, and I will pick it up that afternoon. He sometimes says that it will not work on that day, then I will say that it will be Tuesday, and he will often say that Wednesday will work.
《青春集结号》讲述的是95后军校孩子们的成长生活，“军校生”们在训练、考核、日常生活中相互较劲，训练中的意外丛生、男生女生间的误会不断，让平静的军校因为各路人马的存在波澜不断。成长需要磨难，当新生逐渐适应军校生活，磨合过后又有新的问题不断产生。新兴思想与军校的规定格格不入，是默默忍受还是奋起反抗？爱情的出现，是命运的转折还是墨守成规下的牺牲品？《青春集结号》将展现当代军校生的青春物语，带领观众们感受这一群少男少女成长和蜕变的过程。
女演员“千层套路”倒追男医生？韫北夫妇高段位互宠，全甜无虐每一秒都是心动警报！
As the confirmer of the correction result, the correction result confirmer must timely and comprehensively confirm the correction result according to the time limit agreed in advance.
《黑礁第二季》承接了第一季《黑礁》的故事内容，于2006年10月2日 - 12月18日在日本播出。
讲述了尹泰悟(珉豪 饰)、韩松伊(朴素丹 饰)、徐智安(金珉载 饰)、崔勋(李利敬 饰)、吴佳琳(赵惠贞 饰)、柳世贤(郑柔真 饰)带著各自的理由将尹泰悟独居的阁楼当成秘密根据地，以各自的方式体验人生逐渐成长的故事。
募兵制规定：征召入伍者，虚岁年满十八以上、五十五以下。
……ps：谢谢大家一直的支持。
"Do you mean that these 'dogs' that attacked position 142 are indeed some animals similar in appearance to common dogs?" I said.
张杨向皇帝告假，亲自出城接了周夫子，迎进家门，和张槐陪着，周菡姐弟则另由黄瓜黄豆红椒他们等招待。
第三者的痛苦
すみません、握手して下さい 岡本信人 今井里美
王治乾有些犹豫道：网络小说能有这样火爆的人气。
林聪心里一喜，秦旷却愣了，不知她为何又改主意了。
哈利·波特（丹尼尔·雷德克里夫 饰）即将在霍格沃兹渡过第三个年头，此时在阿兹塔班却传出恶棍小天狼星（加里·奥德曼 饰）越狱的消息。据说小天狼星正是背叛哈利父母的好友，他的教父，而这次小天狼星越狱似乎正是为了找他。哈利的心里悄悄的滋生了为父母报仇的想法，期待着小天狼星的出现。
Love you don't know how to live or die love you smelly shameless
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.
Taidao 3.3
