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scikit-learn: machine learning in Python



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

The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed. See the AUTHORS.rst 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, setuptools, NumPy >= 1.2, SciPy >= 0.7 and a working C++ compiler.

To run the tests you will also need nose >= 0.10.


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 the latest sources with the command:

git clone git://

or if you have write privileges:

git clone


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


After installation, you can launch the test suite from outside the source directory (you will need to have nosetest installed):

python -c "import scikits.learn as skl; skl.test()"

See web page for more information.

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