shogun-cmdline-static – 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 is the Readline package.

Package availability chart
Distribution Base version Our version Architectures
Debian GNU/Linux 7.0 (wheezy)   1.1.0-6~nd70+1 i386, amd64
Debian GNU/Linux 8.0 (jessie) 3.2.0-7.3 1.1.0-6~nd70+1 i386, amd64
Debian testing (buster) 3.2.0-7.5    
Debian unstable (sid) 3.2.0-7.5    
Ubuntu 12.04 LTS “Precise Pangolin” (precise) 1.1.0-4ubuntu2    
Ubuntu 14.04 “Trusty Tahr” (trusty) 3.1.1-1    
Ubuntu 16.04 “Xenial Xerus” (xenial) 3.2.0-7.3build4    
Ubuntu 16.10 “Yakkety Yak” (yakkety) 3.2.0-7.3ubuntu2    
Ubuntu 17.04 “Zesty Zapus” (zesty) 3.2.0-7.4    
Ubuntu 17.10 “Artful Aardvark” (artful) 3.2.0-7.5    

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