The SHOGUN machine learning toolbox
Unified and efficient Machine Learning since 1999.
Develop branch build status:
Donate to Shogun via NumFocus:
- See doc/readme/ABOUT.md for a project description.
- See doc/readme/INSTALL.md for installation instructions.
- See doc/readme/INTERFACES.md for calling Shogun from its interfaces.
- See doc/readme/EXAMPLES.md for details on creating API examples.
See doc/readme/DEVELOPING.md for how to hack Shogun.
See API examples for API examples for all interfaces.
- See the wiki for extended developer information.
|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.
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- applications - applications of SHOGUN (outdated)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