Comments (3)
default的model是用的NeuMF-pre (用了pre-trained weights),所以必须要先train完GMF和MLP,如果不想用pre-train,可以直接 set model=NeuMF-end (end-to-end training).
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非常感谢您的回复,不好意思,我是名初学者,能听懂您的意思,具体怎么操作有点困难,我希望先按照您上传的文件简单运行一下,然后学习学习,发现几个小问题:
1.运行语句 python main.py --batch_size=256 --lr=0.001 --embed_size=16,报错说embed_size参数不存在,我是做删除处理的
2.报错说Data文件没有,所以我去论文github项目下载了Data文件,添加到了您的文件夹里
3.报错这句代码assert os.path.exists(config.GMF_model_path), "lack of GMF model"有问题,问题是AssertionError: lack of GMF model,所有我查看了config.py文件,以为和之前Data文件一样是缺少,
所以向您询问了下,说实话,接下来我不知怎么处理了,如果您能指点一二,我将十分感激!谢谢
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- embed_size是我写错了,马上更正,应该是factor_num;
- Data文件我readme里说了,要去Xiangnan He那下载;
- 最简单的解决方式,不用pre-train,具体参考Xiangnan WWW17 paper,config.py中设置model='NeuMF-end'.
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Related Issues (20)
- How to determine the hyper-parameters? HOT 1
- How to extract prediction from this model? HOT 2
- Data files? HOT 1
- RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase.
- Concatenation of user and item embeddings HOT 2
- what is the meaning of num_neg and test_num_neg?
- why did you use kaiming_uniform to init parameters? HOT 1
- a error about use pretraining HOT 3
- Do your code with pytorch have the HOT 1
- Why I use the same code and parameters,the result is not as good as yours? HOT 5
- another issue HOT 1
- It seems that you didn't use the dataset of test_rating,can you show why? HOT 1
- 向量生成 HOT 2
- user_vector HOT 1
- Broken pipe error
- Haven't used sigmoid in the output of last layer. HOT 1
- main_path和model_path
- the NCF wasn't good when I using pre-trained
- 请问evaluation_threads = 1 # mp.cpu_count()这里可以调整为多线程吗?
- GMF better than BPR HOT 3
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