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scikit-learn: machine learning in Python

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README.rst

About

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.

Download

You can download source code and Windows binaries from SourceForge:

http://sourceforge.net/projects/scikit-learn/files/

Dependencies

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/).

Install

This packages uses distutils, which is the default way of installing python modules. The install command is:

python setup.py install

Mailing list

There's a general and development mailing list, visit https://lists.sourceforge.net/lists/listinfo/scikit-learn-general to subscribe to the mailing list.

IRC channel

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.

Development

Code

GIT

You can check out the current repository with the command:

git clone git://scikit-learn.git.sourceforge.net/gitroot/scikit-learn/scikit-learn

Developers with write privileges should instead use the command:

git clone ssh://USERNAME@scikit-learn.git.sourceforge.net/gitroot/scikit-learn/scikit-learn

where USERNAME is your sourceforge username.

Bugs

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

Testing

To execute the test suite, run from the project's top directory (you will need to have nosetest installed):

python setup.py test
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