项目作者: guoyang9

项目描述 :
A pytorch implementation for BPR (Bayesian Personalized Ranking).
高级语言: Python
项目地址: git://github.com/guoyang9/BPR-pytorch.git
创建时间: 2019-06-17T02:49:13Z
项目社区:https://github.com/guoyang9/BPR-pytorch

开源协议:

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Pytorch-BPR

Note that I use the two sub datasets provided by Xiangnan’s repo. Another pytorch NCF implementaion can be found at this repo.

I utilized a factor number 32, and posted the results in the NCF paper and this implementation here. Since there is no specific numbers in their paper, I found this implementation achieved a better performance than the original curve. Moreover, the batch_size is not very sensitive with the final model performance.

Models MovieLens HR@10 MovieLens NDCG@10 Pinterest HR@10 Pinterest NDCG@10
pytorch-BPR 0.700 0.418 0.877 0.551

The requirements are as follows:

  1. * python==3.6
  2. * pandas==0.24.2
  3. * numpy==1.16.2
  4. * pytorch==1.0.1
  5. * tensorboardX==1.6 (mainly useful when you want to visulize the loss, see https://github.com/lanpa/tensorboard-pytorch)

Example to run:

  1. python main.py --factor_num=16 --lamda=0.001