Distributed Factorization Machines
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Latest commit 78e3562 Mar 24, 2016 @mli mli don't build test in default


Distributed Factorization Machines

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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


Origins from wormhole/learn/difacto.

(NOTE: this project is still under developing)


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