scikits.learn is a python module for machine learning built on top of scipy.
The project was started in 2007 by David Cournapeu as a Google Summer of Code project, and since then many volunteers have contributed. See the AUTHORS file for a complete list of contributors.
It is currently maintained by a team of volunteers.
You can download source code and Windows binaries from SourceForge:
http://sourceforge.net/projects/scikit-learn/files/
The required dependencies to build the software are python >= 2.5, NumPy >= 1.1, SciPy and a working C++ compiler.
Optional dependencies are scikits.optimization and the Boost libraries for module scikits.learn.manifold.
To run the tests you will also need nosetests and python-dap (http://pypi.python.org/pypi/dap/).
This packages uses distutils, which is the default way of installing python modules. The install command is:
python setup.py install
There's a general and development mailing list, visit https://lists.sourceforge.net/lists/listinfo/scikit-learn-general to subscribe to the mailing list.
Some developers tend to hang around the channel #scikit-learn
at irc.freenode.net, especially during the week preparing a new
release. If nobody is available to answer your questions there don't
hesitate to ask it on the mailing list to reach a wider audience.
You can check the latest sources with the command:
git clone git://github.com/scikit-learn/scikit-learn.git
or if you have write privileges:
git clone [email protected]:scikit-learn/scikit-learn.git
Please submit bugs you might encounter, as well as patches and feature requests to the tracker located at the address https://sourceforge.net/apps/trac/scikit-learn/report
To execute the test suite, run from the project's top directory (you will need to have nosetest installed):
python setup.py test