A short paper describing the library is now available on arXiv http://arxiv.org/abs/1505.00641
This repository contains the python interface. Please have a look at https://github.com/ibayer/fastFM-core if you are interessed in the command line interface or the solver source code (implemented in C).
This repository relays on sub-repositories just using git clone .. doesn't fetch them.
use: git clone --recursive https://github.com/ibayer/fastFM.git
Or do the two-step dance if you wish. You need to run git submodule update --init --recursive from within the fastFM-core/ folder in order to clone them as well.
- scikit-learn
- numpy
- scipy
- pandas
- cython
install with pip install -r /fastFM/requirements.txt
- CXSparse (included as submodule)
- glib-2.0
This worked on ubuntu 14.04: sudo apt-get install libglib2.0-dev libatlas-base-dev python-dev
First build the C libraries: (cd fastFM/; make)
For development install the lib inplace:
(Run the following command from the same directory as git clone before.)
pip install -e fastFM/
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. (Contributed by altimin)
It should be possible to compile the library on Windows. I'm developing on linux but have received multiple requests from people who want to run this library on other platforms. Please let me know about issues you ran into or how you manged to compile on other platfroms (or just open a PR) so that we include this information here.
pick your favorite test runner
cd /fastFM/fastFM/tests/; py.test or
cd /fastFM/fastFM/tests/; nosetests
Please have a look add the files in /fastFM/fastFM/tests/ for examples on how to use FMs for different tasks.