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scikit-learn: machine learning in Python

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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.


You can download source code and Windows binaries from SourceForge:


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 (


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

python install

Mailing list

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

IRC channel

Some developers tend to hang around the channel #scikit-learn at, 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.




You can check out the current repository with the command:

git clone git://

Developers with write privileges should instead use the command:

git clone ssh://

where USERNAME is your sourceforge username.


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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