Not Rated
SHOGUN - is a new machine learning toolbox with focus on large scale kernel methods and especially on Support Vector Machines (SVM) with focus to bioinformatics. It provides a generic SVM object interfacing to several different SVM implementations. Each of the SVMs can be combined with a variety of the many kernels implemented. It can deal with weighted linear combination of a number of sub-kernels, each of which not necessarily working on the same domain, where an optimal sub-kernel weighting can be learned using Multiple Kernel Learning. Apart from SVM 2-class classification and regression problems, a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons and also algorithms to train hidden markov models are implemented. The input feature-objects can be dense, sparse or strings and of type int/short/double/char and can be converted into different feature types. Chains of preprocessors (e.g. substracting the mean) can be attached to each feature object allowing for on-the-fly pre-processing.

SHOGUN comes in different flavours, a stand-a-lone version and also with interfaces to Matlab(tm), R, Octave, Readline and Python. This is the static Python package without using swig.
Associated Programs
Python interactive high-level object-oriented language (default version)
python-matplotlib Python based plotting system in a style similar to Matlab
Available deb Repositories (how-to add a respository)
Debian 32-bit 64-bit
stable 0.9.3-4 0.9.3-4

Ubuntu 32-bit 64-bit
lucid 0.9.1-1build1 0.9.1-1build1

Rating: Not Rated (0 votes)

Login or Register to rate shogun-python, add a Tag, or designate as an alternative to a Windows app

Upload Screenshots
Images must be in GIF, JPG, or PNG formats and can be no larger than 2 MB. Only one file can be uploaded at a time. A description can be included, but it is optional.
You must login or register to upload a screenshot.
Submit Web Links
Submit the title and link (including http://) to an article pertaining to shogun-python and it will appear in the Web Links section of the right banner. Contact us here if an entry needs to be removed.
You must login or register to post links.