Awesome
<img src=https://raw.githubusercontent.com/dmlc/dmlc.github.io/master/img/logo-m/difacto.png width=130/> Distributed Factorization Machines
Fast and memory efficient library for factorization machines (FM).
- Supports both ℓ1 regularized logistic regression and factorization machines.
- Runs on local machine and distributed clusters.
- Scales to datasets with billions examples and features.
Quick Start
The following commands clone and build difacto, then download a sample dataset, and train FM with 2-dimension on it.
git clone --recursive https://github.com/dmlc/difacto
cd difacto; git submodule update --init; make -j8
./tools/download.sh gisette
build/difacto data_in=data/gisette_scale val_data=data/gisette_scale.t lr=.02 V_dim=2 V_lr=.001
History
Origins from wormhole/learn/difacto.
(NOTE: this project is still under developing)
References
Mu Li, Ziqi Liu, Alex Smola, and Yu-Xiang Wang. DiFacto — Distributed Factorization Machines. In WSDM, 2016