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Package: shogun-octave (0.9.1-1 and others)

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 Octave package.

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Download shogun-octave

Download for all available architectures
Architecture Version Package Size Installed Size Files
amd64 0.9.1-1 105.1 kB904 kB [list of files]
armel 0.9.1-1 99.7 kB884 kB [list of files]
hppa 0.9.1-1 108.0 kB912 kB [list of files]
i386 0.9.1-1 102.8 kB888 kB [list of files]
ia64 0.9.1-1 117.7 kB1020 kB [list of files]
mips 0.9.1-1 96.8 kB916 kB [list of files]
mipsel 0.9.1-1 94.5 kB916 kB [list of files]
powerpc 0.9.1-1+b1 104.2 kB908 kB [list of files]
s390 0.9.1-1 102.3 kB908 kB [list of files]
sparc 0.9.1-1 99.6 kB884 kB [list of files]