The Shogun Machine Learning Toolbox
# The SHOGUN machine learning toolbox
Unified and efficient Machine Learning since 1999.
Develop branch build status:
- 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 the cookbook for API examples for all interfaces.
- See the wiki for developer information.
| Interface | Status | |:—————-:|———————————————————–| |python | mature (no known problems) | |octave | mature (no known problems) | |java | 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.
- doc - readmes (doc/reamde, submodule), ipython notebooks, cookbook (api examples), licenses
- examples - example files for all interfaces.
- data - data sets (submodule required for some examples / applications)
- tests - unit and integration tests.
- applications - applications of SHOGUN.
- benchmarks - speed benchmarks.
- cmake - cmake build scripts
Shogun is generally licensed under the GPL3, with code borrowed from various external libraries, and optional parts that are neither compatible with GPL nor BSD. It is possible to compile a BSD3 compatible build of Shogun.
See doc/licenses for details.