Collaborative Filtering On Netflix
评估指标
AUC
PSP@10
Recall@10
Recall@100
nDCG@10
nDCG@100
评测结果
各个模型在此基准测试上的表现结果
比较表格
| 模型名称 | AUC | PSP@10 | Recall@10 | Recall@100 | nDCG@10 | nDCG@100 |
|---|---|---|---|---|---|---|
| infinite-recommendation-networks-a-data | 0.9728 | 0.0375 | 0.2969 | 0.5088 | 0.3059 | 0.3659 |
| towards-amortized-ranking-critical-training | - | - | - | - | - | 0.392 |
| recvae-a-new-variational-autoencoder-for-top | - | - | - | - | - | 0.394 |
| enhancing-vaes-for-collaborative-filtering | - | - | - | - | - | 0.40861 |
| variational-autoencoders-for-collaborative | - | - | - | - | - | 0.380 |
| collaborative-similarity-embedding-for | - | - | 0.2014 | - | - | - |
| 190503375 | - | - | - | - | - | 0.393 |
| variational-autoencoders-for-collaborative | - | - | - | - | - | 0.386 |
| collaborative-metric-learning | - | - | 0.4612 | - | 0.2948 | - |
| latent-relational-metric-learning-via-memory | - | - | 0.5371 | - | 0.3578 | - |