Click-Through Rate Prediction on Company*

Metric: Log Loss (lower is better)

LeaderboardDataset

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#	Model↕	Log Loss▲	Extra Data	Paper	Date↕	Code
1	DeepFM	0.02618	No	DeepFM: A Factorization-Machine based Neural Net...	2017-03-13	Code
2	FNN	0.02629	No	Deep Learning over Multi-field Categorical Data:...	2016-01-11	Code
3	Wide & Deep (LR & DNN)	0.02634	No	Wide & Deep Learning for Recommender Systems	2016-06-24	Code
4	PNN*	0.02636	No	Product-based Neural Networks for User Response ...	2016-11-01	Code
5	IPNN	0.02637	No	Product-based Neural Networks for User Response ...	2016-11-01	Code
6	Wide & Deep (FM & DNN)	0.0264	No	Wide & Deep Learning for Recommender Systems	2016-06-24	Code
7	OPNN	0.02641	No	Product-based Neural Networks for User Response ...	2016-11-01	Code
8	DeepMCP	0.2341	No	Representation Learning-Assisted Click-Through R...	2019-06-11	Code

#1DeepFMSOTA
0.02618
Log Loss· 2017-03-13
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction Code
#2FNNSOTA
0.02629
Log Loss· 2016-01-11
Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction Code
#3Wide & Deep (LR & DNN)
0.02634
Log Loss· 2016-06-24
Wide & Deep Learning for Recommender Systems Code
#4PNN*
0.02636
Log Loss· 2016-11-01
Product-based Neural Networks for User Response Prediction Code
#5IPNN
0.02637
Log Loss· 2016-11-01
Product-based Neural Networks for User Response Prediction Code
#6Wide & Deep (FM & DNN)
0.0264
Log Loss· 2016-06-24
Wide & Deep Learning for Recommender Systems Code
#7OPNN
0.02641
Log Loss· 2016-11-01
Product-based Neural Networks for User Response Prediction Code
#8DeepMCP
0.2341
Log Loss· 2019-06-11
Representation Learning-Assisted Click-Through Rate Prediction Code