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scikit-learn: machine learning in Python

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.. -*- mode: rst -*-


scikit.learn is a python module for machine learning built on top of

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'


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

To run the tests you will also need nosetests and python-dap


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

  python 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 build_ext --include=/opt/local/include
  python install

Mailing list

There's a general and development mailing list, visit to
subscribe to the mailing list.



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

   svn co scikit-learn

You can also browse the code online in the address


Please submit bugs you might encounter, as well as patches and feature
requests to the tracker located at the address


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

    python test

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