Click Through Rate Prediction On Movielens
Metriken
AUC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||
|---|---|---|
| github.com/guotong1988/movielens_dataset | 0.79 | - |
| DIN + Dice Activation | 0.7348 | Deep Interest Network for Click-Through Rate Prediction |
| DIN | 0.7337 | Deep Interest Network for Click-Through Rate Prediction |
| DeepFM | 0.7324 | DeepFM: A Factorization-Machine based Neural Network for CTR Prediction |
| PNN | 0.7321 | Product-based Neural Networks for User Response Prediction |
| Wide & Deep | 0.7304 | Wide & Deep Learning for Recommender Systems |
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