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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 package contains debug symbols for all interfaces.

Package version:0.6.3-1


Explanation of directory content

README   - this file
Makefile - to create release archives
src      - shogun source code
doc      - documentation (to be built using doxygen)
examples - example files for all interfaces

testsuite - the shogun test suite

The following table depicts the status of each interface available in shogun:



shogun (0.6.3-1) unstable; urgency=low

  * New upstream bugfix version.
  * Adapt for new directory layout.
  * Run tests for all interfaces on make install.
  * Add doc-base file.
  * Add patch target and bump Standards Version to 3.8.0.
  * Add fix from trunk to fix return values in R interface.

 -- Soeren Sonnenburg <>  Wed, 18 Jun 2008 12:04:16 +0200

shogun (0.6.2-1) unstable; 


This program was downloaded from
The main upstream Author is Soeren Sonnenburg <>.

Copyright: (c) 1999-2008 Fraunhofer Institute FIRST and Max-Planck-Society


    This program is free software; you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation; eithe

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