LIBFFM: A Library for Field-aware Factorization Machines

Machine Learning Group at National Taiwan University


LIBFFM is an open source tool for field-aware factorization machines (FFM). For the formulation of FFM, please see this paper. It has been used to win the top-3 in recent click-through rate prediction competitions (Criteo, Avazu, Outbrain, and RecSys 2015).

It supports

Main features include


Warning: FFM is prone to overfitting. See README in the package before using.

Please download LIBFFM at github.

Branches and Interfaces

Description Version Developer Link
A branch for regression problems 1.12 LIBFFM authors zip or tar.gz
A Python wrapper to run LIBFFM on SFrames N/A Chris DuBois link
A branch that includes linear and bias terms 1.14 LIBFFM authors zip or tar.gz
A branch that implements standard FM 1.22 LIBFFM authors zip or tar.gz

Please contact Yuchin Juan for questions, comments, feature requests, or bug report. For Windows related questions please send your email to Wei-sheng Chin.