Click Through Rate Prediction On Dianping
评估指标
AUC
Log Loss
评测结果
各个模型在此基准测试上的表现结果
模型名称 | AUC | Log Loss | Paper Title | Repository |
|---|---|---|---|---|
| Wide & Deep | 0.8361 | 0.3364 | Wide & Deep Learning for Recommender Systems | |
| DeepFM | 0.8481 | 0.3333 | DeepFM: A Factorization-Machine based Neural Network for CTR Prediction | |
| PNN | 0.8445 | 0.3424 | Product-based Neural Networks for User Response Prediction | |
| DNN | 0.8318 | - | xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems | |
| xDeepFM | 0.8639 | 0.3156 | xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems |
0 of 5 row(s) selected.