Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction
2019-04-09Code Available0· sign in to hype
Bin Liu, Ruiming Tang, Yingzhi Chen, Jinkai Yu, Huifeng Guo, Yuzhou Zhang
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/shenweichen/DeepCTRtf★ 8,006
- github.com/xue-pai/FuxiCTRpytorch★ 1,379
- github.com/UlionTse/mlgbpytorch★ 1,049
- github.com/chenjiyan2001/paddle-FGCNNpaddle★ 1
- github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/fgcnnpaddle★ 0
- github.com/shenweichen/DeepCTR-PyTorchpytorch★ 0
Abstract
Easy-to-use,Modular and Extendible package of deep-learning based CTR models.DeepFM,DeepInterestNetwork(DIN),DeepInterestEvolutionNetwork(DIEN),DeepCrossNetwork(DCN),AttentionalFactorizationMachine(AFM),Neural Factorization Machine(NFM),AutoInt,Deep Session Interest Network(DSIN)
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| Avazu | FGCNN+IPNN | AUC | 0.79 | — | Unverified |
| Huawei App Store | FGCNN+IPNN | AUC | 0.94 | — | Unverified |