Comments (1)
这个问题不太好定位具体的原因。在训练样本相同的情况下,至少还有两个因素值得探讨:
#1 模型capacity
模型的学习/表达能力,能学多少
#2 trainability
可训练性,这是一个优化问题,能不能找到一个“好”的解;很多模型架构的表达能力都是同等的,性能上的差异都是由于某些结构比其他架构更容易优化导致的。
你说的理论上更高,应该指的是DeepFM的表达能力更强;但是可训练性问题也是客观存在的,比如调参。当然,也不排除代码有bug。
PS:有同学反馈FM part输出K为向量与Deep-part concat起来送入输出层有进一步提升。
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