Click Through Rate Prediction On Frappe
Metriken
AUC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||
|---|---|---|
| TF4CTR | 0.9872 | TF4CTR: Twin Focus Framework for CTR Prediction via Adaptive Sample Differentiation |
| FinalMLP | 0.9861 | FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction |
| FinalMLP + MMBAttn | 0.9861 | MMBAttn: Max-Mean and Bit-wise Attention for CTR Prediction |
| DNN + MMBAttn | 0.985 | MMBAttn: Max-Mean and Bit-wise Attention for CTR Prediction |
| AFN+ | 0.9783 | Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions |
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