Click-Through Rate Prediction on MovieLens 20M

Metric: AUC (higher is better)

LeaderboardDataset

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#	Model↕	AUC▼	Extra Data	Paper	Date↕	Code
1	github.com/guotong1988/movielens_dataset	0.79	No	-	-	-
2	DIN + Dice Activation	0.7348	No	Deep Interest Network for Click-Through Rate Pre...	2017-06-21	Code
3	DIN	0.7337	No	Deep Interest Network for Click-Through Rate Pre...	2017-06-21	Code
4	DeepFM	0.7324	No	DeepFM: A Factorization-Machine based Neural Net...	2017-03-13	Code
5	PNN	0.7321	No	Product-based Neural Networks for User Response ...	2016-11-01	Code
6	Wide & Deep	0.7304	No	Wide & Deep Learning for Recommender Systems	2016-06-24	Code

#1github.com/guotong1988/movielens_dataset
0.79
AUC
No paper
#2DIN + Dice ActivationSOTA
0.7348
AUC· 2017-06-21
Deep Interest Network for Click-Through Rate Prediction Code
#3DIN
0.7337
AUC· 2017-06-21
Deep Interest Network for Click-Through Rate Prediction Code
#4DeepFMSOTA
0.7324
AUC· 2017-03-13
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction Code
#5PNNSOTA
0.7321
AUC· 2016-11-01
Product-based Neural Networks for User Response Prediction Code
#6Wide & DeepSOTA
0.7304
AUC· 2016-06-24
Wide & Deep Learning for Recommender Systems Code