Skip to content
Sections
>> Trisquel >> Packages >> etiona >> libdevel >> libshogun-dev
etiona  ]
[ Source: shogun  ]

Package: libshogun-dev (3.2.0-7.5)

Large Scale Machine Learning Toolbox

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 package includes the developer files required to create stand-a-lone executables.

Other Packages Related to libshogun-dev

  • depends
  • recommends
  • suggests
  • dep: libshogun16 (= 3.2.0-7.5)
    Large Scale Machine Learning Toolbox

Download libshogun-dev

Download for all available architectures
Architecture Package Size Installed Size Files
amd64 593.0 kB4298 kB [list of files]
i386 593.0 kB4298 kB [list of files]