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scikit-learn: machine learning in Python
C Python C++

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README

.. -*- mode: 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 volonteers.


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, the Boost libraries and a working C++ compiler.

Optional dependencies are scikits.optimization for module
machine.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.


Development
===========

Code
----

To check out the sources for subversion run the command::

   svn co http://scikit-learn.svn.sourceforge.net/svnroot/scikit-learn/trunk scikit-learn

You can also browse the code online in the address
http://scikit-learn.svn.sourceforge.net/viewvc/scikit-learn


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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