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Package: shogun-cmdline (0.10.0-2.1 and others)

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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.

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Download for all available architectures
Architecture Version Package Size Installed Size Files
alpha (unofficial port) 0.10.0-2.1 43.8 kB180.0 kB [list of files]
hppa (unofficial port) 0.10.0-2 46.7 kB424.0 kB [list of files]
ia64 0.10.0-2.1 45.0 kB1,296.0 kB [list of files]
kfreebsd-amd64 0.10.0-2.1 43.3 kB246.0 kB [list of files]
kfreebsd-i386 0.10.0-2.1 42.4 kB244.0 kB [list of files]
mips 0.10.0-2.1 41.8 kB408.0 kB [list of files]
mipsel 0.10.0-2.1 40.4 kB408.0 kB [list of files]
powerpcspe (unofficial port) 0.10.0-2 42.8 kB404.0 kB [list of files]
sh4 (unofficial port) 0.10.0-2.1+b1 44.2 kB408.0 kB [list of files]