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 a team of volonteers.

There are currently no public releases, please see section 'Code' below.

The required dependencies to build the software are python >= 2.5, NumPy >= 1.1, SciPy, the Boost libraries and a working C++ compiler.

Optional dependencies are scikits.optimization for module machine.manifold_learning.

To run the tests you will also need nosetests and python-dap (http:https://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

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 commands:

python setup.py build_ext --include=/opt/local/include
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.

To check out the sources for subversion run 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 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