rixwew/pytorch-fm

Factorization Machine models in PyTorch

Python

1,081

32 commits

updated Apr 8, 2024

See the code

README

Factorization Machine models in PyTorch

This package provides a PyTorch implementation of factorization machine models and common datasets in CTR prediction.

Available Datasets

Available Models

Model	Reference
Logistic Regression
Factorization Machine	S Rendle, Factorization Machines, 2010.
Field-aware Factorization Machine	Y Juan, et al. Field-aware Factorization Machines for CTR Prediction, 2015.
Higher-Order Factorization Machines	M Blondel, et al. Higher-Order Factorization Machines, 2016.
Factorization-Supported Neural Network	W Zhang, et al. Deep Learning over Multi-field Categorical Data - A Case Study on User Response Prediction, 2016.
Wide&Deep	HT Cheng, et al. Wide & Deep Learning for Recommender Systems, 2016.
Attentional Factorization Machine	J Xiao, et al. Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks, 2017.
Neural Factorization Machine	X He and TS Chua, Neural Factorization Machines for Sparse Predictive Analytics, 2017.
Neural Collaborative Filtering	X He, et al. Neural Collaborative Filtering, 2017.
Field-aware Neural Factorization Machine	L Zhang, et al. Field-aware Neural Factorization Machine for Click-Through Rate Prediction, 2019.
Product Neural Network	Y Qu, et al. Product-based Neural Networks for User Response Prediction, 2016.
Deep Cross Network	R Wang, et al. Deep & Cross Network for Ad Click Predictions, 2017.
DeepFM	H Guo, et al. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction, 2017.
xDeepFM	J Lian, et al. xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems, 2018.
AutoInt (Automatic Feature Interaction Model)	W Song, et al. AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks, 2018.
AFN(AdaptiveFactorizationNetwork Model)	Cheng W, et al. Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions, AAAI'20.

Each model's AUC values are about 0.80 for criteo dataset, and about 0.78 for avazu dataset. (please see example code)

Installation

pip install torchfm

API Documentation

https://rixwew.github.io/pytorch-fm

Licence

MIT

autoint

avazu-dataset

collaborative-filtering

criteo-dataset

ctr-prediction

dcn

deepfm

factorization-machines

ffm

fnfm

hofm

movielens-dataset

neural-collaborative-filtering

nfm

pnn

pytorch

xdeepfm

Contributors

rixwew

23 commits

yfreedomliTHU

7 commits

Drone-Banks

2 commits

Similar repos

Prayforhanluo/CTR_Algorithm

一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM, xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt,…

279

p768lwy3/torecsys

ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not…

106

fuhailin/awesome-RecSys

Must-read papers on recommendation systems (RecSys)

284

yinyajun/Details-In-Recommendation

Recommender-In-Detail is a package which offers detailed implementations of state-of-the-art…

nusdbsystem/ARM-Net

A ready-to-use framework of the state-of-the-art models for structured (tabular) data learning with…

QunBB/RecSys

This project is about recommendation system including rank&match models and metrics which are all…

CHIANGEL/Research-Paper-Note

My research paper notes, focusing on data mining/recommender/reinforcement learning.…

Gavince/Recommend-System

深度学习与推荐系统学习，理论结合代码更香。

164

Languages

Python

100.0%

rixwew/pytorch-fm

Factorization Machine models in PyTorch

Python

1,081

32 commits

updated Apr 8, 2024

See the code

README

Factorization Machine models in PyTorch

This package provides a PyTorch implementation of factorization machine models and common datasets in CTR prediction.

Available Datasets

Available Models

Model	Reference
Logistic Regression
Factorization Machine	S Rendle, Factorization Machines, 2010.
Field-aware Factorization Machine	Y Juan, et al. Field-aware Factorization Machines for CTR Prediction, 2015.
Higher-Order Factorization Machines	M Blondel, et al. Higher-Order Factorization Machines, 2016.
Factorization-Supported Neural Network	W Zhang, et al. Deep Learning over Multi-field Categorical Data - A Case Study on User Response Prediction, 2016.
Wide&Deep	HT Cheng, et al. Wide & Deep Learning for Recommender Systems, 2016.
Attentional Factorization Machine	J Xiao, et al. Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks, 2017.
Neural Factorization Machine	X He and TS Chua, Neural Factorization Machines for Sparse Predictive Analytics, 2017.
Neural Collaborative Filtering	X He, et al. Neural Collaborative Filtering, 2017.
Field-aware Neural Factorization Machine	L Zhang, et al. Field-aware Neural Factorization Machine for Click-Through Rate Prediction, 2019.
Product Neural Network	Y Qu, et al. Product-based Neural Networks for User Response Prediction, 2016.
Deep Cross Network	R Wang, et al. Deep & Cross Network for Ad Click Predictions, 2017.
DeepFM	H Guo, et al. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction, 2017.
xDeepFM	J Lian, et al. xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems, 2018.
AutoInt (Automatic Feature Interaction Model)	W Song, et al. AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks, 2018.
AFN(AdaptiveFactorizationNetwork Model)	Cheng W, et al. Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions, AAAI'20.

Each model's AUC values are about 0.80 for criteo dataset, and about 0.78 for avazu dataset. (please see example code)

Installation

pip install torchfm

API Documentation

https://rixwew.github.io/pytorch-fm

Licence

MIT

autoint

avazu-dataset

collaborative-filtering

criteo-dataset

ctr-prediction

dcn

deepfm

factorization-machines

ffm

fnfm

hofm

movielens-dataset

neural-collaborative-filtering

nfm

pnn

pytorch

xdeepfm

Similar repos

Prayforhanluo/CTR_Algorithm

一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM, xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt,…

279

p768lwy3/torecsys

ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not…

106

fuhailin/awesome-RecSys

Must-read papers on recommendation systems (RecSys)

284

yinyajun/Details-In-Recommendation

Recommender-In-Detail is a package which offers detailed implementations of state-of-the-art…

nusdbsystem/ARM-Net

A ready-to-use framework of the state-of-the-art models for structured (tabular) data learning with…

QunBB/RecSys

This project is about recommendation system including rank&match models and metrics which are all…

CHIANGEL/Research-Paper-Note

My research paper notes, focusing on data mining/recommender/reinforcement learning.…

Gavince/Recommend-System

深度学习与推荐系统学习，理论结合代码更香。

164

Contributors

rixwew

23 commits

yfreedomliTHU

7 commits

Drone-Banks

2 commits

Languages

Python

100.0%