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我银子被人骗了，也不大敢在街上乱逛。隔壁的板栗伸头过来想问他话儿，见他出神，就瞄向那书页，原来是吕蒙正的《破窑赋》，于是笑问道：如何，没看过这文？葫芦摇头道：怕是姑姑读了顺手搁这的。At present, the progress of farmers in the society is the progress of the countryside. Improving the quality of farmers is the fundamental plan to realize the economic development, social progress and long-term stability in the countryside. Therefore, the work of popularizing education for all must be carried out attentively. The improvement and progress of the quality of the whole peasant team mainly depends on the progress and improvement of the young people. They are creative and full of vitality. They are representatives of the new rural productive forces and contain huge human resources. Stabilizing and strengthening agriculture and improving its comprehensive production potential require them to cultivate. To increase farmers' income and lead a rich and polite life, they need to explore. To strengthen the construction of democracy and legal system and spiritual courtesy at the grass-roots level in rural areas and to maintain rural stability, they need to play an attentive role. Therefore, the quality of the vast number of rural youth and whether their intentions and creativity can be brought into play are directly related to the smooth realization of the cross-century development goals of China's agriculture and rural areas.秦旷听了黯然，是啊，他连娶谁都无法做主。　　葵 德川三代是日本放送协会|NHK在2000年年制作播放的第39部NHK大河剧，播放期间是2000年1月9日 - 12月17日。　　本剧故事是从关原之战之前开始说起，以德川家康、德川秀忠、德川家光祖孙三代为主角，描述在德川幕府成立过程中，丰臣家如何灭亡，以及之後德川家与朝廷之间的关系。前半部可以说是与日本战国相关的戏码，而後半部则是以家庭、政治为主的戏剧。　　第一集全集在演出关原之战当天的情形，而在二到十三集则是回溯关原之战的过程。剧中以中村梅雀饰演的德川光国当解说旁白，叙述其祖的故事。全剧采高画质播出，也使用了许多CG效果。　　本剧可谓是一部相当遵照史实演出的历史剧，采用的主角演员也绝大部份是实力派资深演员。但是因为演员年纪实在太大，尽管演技精湛，却也造成一般观众对此诟病。Upload Sharing Time: 2018-10-13It 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.