scikit.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 Fabian Pedregosa.
There are currently no public releases, please se the section 'Code' below.
To install this package, you will need python >= 2.5, NumPy, the Boost libraries and a working c++ compiler.
In order to run the tests, you will need nosetests, python-dap (http:https://pypi.python.org/pypi/dap/) and sikits.optimization.
This packages uses distutils, which is the default way of installing python modules. The install command is
python setup.py install
If you have installed the boost libraries in a non-standard location you might need to pass the appropriate --include argument so that it find the correct headers. For example, if your headers reside in /opt/local/include, (which is the case if you have installed them through Mac Ports), you must issue the command:
python setup.py build_ext --include=/opt/local/includepython 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.
To check out the sources for subversion, issue the command
svn co http:https://scikit-learn.svn.sourceforge.net/svnroot/scikit-learn/trunk scikit-learn
You can also browse the code online in the address http:https://scikit-learn.svn.sourceforge.net/viewvc/scikit-learn
Please submit bugs you might encounter, as well as patches and feature requests to the tracker located at the address http:https://sourceforge.net/tracker/?group_id=294768
To run the test suite (you will need nosetests), issue the command 'nosetests' from the project's top directory.