If you use this project please give credit by citing:

Immanuel Bayer (2015): fastFM: A Library for Factorization Machines http:https://arxiv.org/abs/1505.00641

This repository contains the source code for the fastFM C library and the stand-alone comand line interface (cli). In general we recommend to use fastFM with the Python interface.

fastFM-core/bin/bin/fastfm data/train_regression data/test_regression \
    --task regression   \
    --rng-seed 1234     \
    --init-var=0.11     \
    --n-iter=123        \
    --solver='mcmc'     \
    --rank 7            \
    --l2-reg=.22

Examples on how to use the other command line options options, including example data, can be found in fastFM-core/demo/Makefile. The demo/ folder contains examples showing how to use fastFM as C library.

Supported solvers and tasks

OS X: Library compiles on OSX, however console interface doesn't.

# Install cblas (Linux only).
$ sudo apt-get libatlas-base-dev

# Clone the repro including submodules (or clone + `git submodule update --init --recursive`)
$ git clone --recursive https://github.com/ibayer/fastFM-core.git

# Build library
$ cd fastFM-core/; make;

# Build command line interface (this works currently only on osx)
$ make cli

OS X: Recommended way to manage dependencies is Homebrew package manager. If you have brew installed, dependencies can be installed by running command brew install glib gsl argp-standalone.

# The tests require the glib and gsl library (Linux, for OSX see above).
$ sudo apt-get libglib2.0-dev libgsl0-dev

$ cd fastFM-core/src/tests

# Build the tests
$ make

# Run all tests
$ make check

• Star this repository: keeps contributors motivated
• Open a issue: report bugs or suggest improvements
• Fix errors in the documentation: small changes matter
• Contribute code

Contributions are very wellcome! Since this project lives on github we reommend to open a pull request (PR) for code contributions as early as possible. This is the fastest way to get feedback and allows Travis CI to run checks on your changes.

• check coding style (google) lang-format-3.5 -style=google -i <YOUR_FILE.c/h>
• static code analysis clang-tidy-3.5 -fix <YOUR_FILE.c/h> -- I.
• run valgrind memory check on sparse_test.c make mem_check
• run valgrind to check for errors valgrind -v ./a.out >& out

Contributors

• takuti
• altimin
• ibayer