Click Through Rate Prediction On Movielens
المقاييس
AUC
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
اسم النموذج | AUC | Paper Title | Repository |
|---|---|---|---|
| Wide & Deep | 0.7304 | Wide & Deep Learning for Recommender Systems | |
| github.com/guotong1988/movielens_dataset | 0.79 | - | - |
| DeepFM | 0.7324 | DeepFM: A Factorization-Machine based Neural Network for CTR Prediction | |
| PNN | 0.7321 | Product-based Neural Networks for User Response Prediction | |
| DIN + Dice Activation | 0.7348 | Deep Interest Network for Click-Through Rate Prediction | |
| DIN | 0.7337 | Deep Interest Network for Click-Through Rate Prediction |
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