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大佬您好,请教数据集划分和训练的问题

大佬您好,阅读了您的硕士论文,代码还没来得及阅读,作为小白想先请教您几个可能比较低级的问题:
1、我看到论文中有写到每个个体的准确率,请问网络训练的时候是每个受试者都用网络单独训练一次测试一次吗?还是所有受试者的1346分窗后放在一起训练(只训练一次网络),然后在每个个体上跑测试得到的?
2、以DB2为例,所有受试者的1346作为训练集,25作为测试集,您觉得会不会不如30个受试者作为训练集,10个受试者作为测试集更能表现网络的泛化能力?因为网络训练完如果实际使用推理的话是用在之前完全没见过的受试者身上的。
最后感谢大佬的开源工作,这对小白来说真的非常有意义!如果可以的话可否再推荐几个肌电分类的开源代码供小白学习(在github上实在找不到很好的ninapro数据集分类代码了。。。),非常感谢!

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