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Difacto

Distributed Factorization Machines

Install / Use

/learn @dmlc/Difacto
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

<img src=https://raw.githubusercontent.com/dmlc/dmlc.github.io/master/img/logo-m/difacto.png width=130/> Distributed Factorization Machines

Build Status codecov.io Documentation Status GitHub license

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

View on GitHub
GitHub Stars299
CategoryDevelopment
Updated3mo ago
Forks89

Languages

C++

Security Score

77/100

Audited on Dec 2, 2025

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