Comments (2)
The maxEpoch provided in mhcn.py is suggested numbers which I used. You can continue training but according to my experience, the best performance has been reached within 120, 30, 30 epochs. In the current version, the early stop mechanism hasn't been provided. I usually set a large maxepoch and record the performance for every epoch. Once the best performance has remained unchanged for 20 epochs (it depends. Sometimes a few methods like LightGCN may take more epochs to jump out the local minimum). I will stop the training.
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Related Issues (20)
- About the code on find_k_largest HOT 3
- Problems of results of LightGCN HOT 4
- error message in MHCN HOT 2
- 关于SimGCL不加入0层卷积(即原始表示)的问题 HOT 1
- Require dataset: DouBan-Book HOT 2
- 性能指标问题 HOT 3
- SimGCL的复现 HOT 3
- Socialmf进行ranking的性能指标问题 HOT 2
- Douban-Book数据集 HOT 9
- 关于baseline复现问题 HOT 2
- item.ranking=on -topN 5,10,15,20,50 的问题 HOT 1
- Hopes new indicators and functions can be added QRec-Evaluation HOT 3
- measure functions
- Distribution of item representation HOT 3
- there's no ratings code for SimGCL HOT 1
- MemoryError for motif matirx in MHCN. HOT 1
- RSGAN中负样本生成的问题 HOT 1
- 使用GPU HOT 2
- K重交叉验证每一次结果不一样 HOT 2
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