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License: MIT License
Detecting Beneficial Feature Interactions for Recommender Systems, AAAI 2021
License: MIT License
This is an interesting work. When I realized the baseline of Frappe data set, I found that the evaluation metrics were better than those reported in this paper. I want to know whether your baseline hyperparameter setting is consistent with the model proposed in this paper or whether grid search is the best.
When I follow the "read me" in code, it turns out with "run out of input". How can I deal with it?
Dear researchers,
I read your paper and it is so interesting. However, I would try to reproduce your experiments and I have on question: I run your code but just achieve the results(auc:0.8942, acc:0.8855 on movie-tags) with 300 epochs, i want to know how to achieve the experiment data in your paper.
Thank you very much,
wangzhen38
请问processed文件里的frappe.dataset是空的吗 它有什么作用
从论文以及代码上看,分类问题也是用MSE_loss,请问我理解的对吗,如果是的话,为什么要这样用呢?
边的权重f_ep,我理解通过L0近似方法得到的是 0 <= s <=1,为什么case study里有负的权重呢?
谢谢~
请问LinkPred类的forward函数中的torch.log2()函数和
s = torch.sigmoid(sum_log/self.temp)
s = s * (self.inter_max - self.inter_min) + self.inter_min
到底是干什么用的呢?
predict_edge
修改为pred_edges
;processed/frappe/
目录下,新建一个空的frappe.dataset
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