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Click-Through Rate Prediction
Click Through Rate Prediction On Ipinyou
Click Through Rate Prediction On Ipinyou
Metrics
AUC
LogLoss
Results
Performance results of various models on this benchmark
Columns
Model Name
AUC
LogLoss
Paper Title
OPNN
0.8174
-
Product-based Neural Networks for User Response Prediction
IPNN
0.7914
-
Product-based Neural Networks for User Response Prediction
DCNv3
0.7856
0.005535
FCN: Fusing Exponential and Linear Cross Network for Click-Through Rate Prediction
OptInter
0.7825
0.005604
Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction
OptInter-M
0.7800
0.00564
Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction
PNN*
0.7661
-
Product-based Neural Networks for User Response Prediction
FNN
0.7619
-
Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction
0 of 7 row(s) selected.
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