CNevd / DiFacto

Distributed Factorization Machines and LR with ps-lite

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/CNevd/DiFacto
cd DiFacto; make -j8
./tools/download.sh gisette
build/difacto xx.conf data_in=data/gisette_scale data_val=data/gisette_scale.t lr=.02 V_dim=2 V_lr=.001

References

Mu Li, Ziqi Liu, Alex Smola, and Yu-Xiang Wang. DiFacto — Distributed Factorization Machines. In WSDM, 2016