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Short Description
Shogun Machine Learning Toolbox runtime environment
Full Description

The SHOGUN machine learning toolbox

Unified and efficient Machine Learning since 1999.

Latest release:

Cite Shogun:

Develop branch build status:

Donate to Shogun via NumFocus:



Shogun is implemented in C++ and offers automatically generated, unified interfaces to Python, Octave, Java / Scala, Ruby, C#, R, Lua. We are currently working on adding more languages including JavaScript, D, and Matlab.

Interface Status
python mature (no known problems)
octave mature (no known problems)
java/scala stable (no known problems)
ruby stable (no known problems)
csharp stable (no known problems)
r beta (most examples work, static calls unavailable)
lua alpha (many examples work, string typemaps are unstable, overloaded methods unavailable)
perl pre-alpha (work in progress quality)
js pre-alpha (work in progress quality)

See our website for examples in all languages.


Shogun is supported under GNU/Linux, MacOSX, FreeBSD, and Windows.
See our buildfarm.

Directory Contents

The following directories are found in the source distribution.
Note that some folders are submodules that can be checked out with
git submodule update --init.

  • src - source code, separated into C++ source and interfaces
  • doc - readmes (doc/reamde, submodule), ipython notebooks, cookbook (api examples), licenses
  • examples - example files for all interfaces
  • data - data sets (submodule, required for examples)
  • tests - unit tests and continuous integration of interface examples
  • applications - applications of SHOGUN (outdated)
  • benchmarks - speed benchmarks
  • cmake - cmake build scripts


Shogun is distributed under BSD 3-clause license, with
optional GPL3 components.
See doc/licenses for details.

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