SHOGUN 0.6.3 (Default branch)
SHOGUN is a machine learning toolbox whose focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It provides a generic SVM object interfacing to several different SVM implementations, all making use of the same underlying, efficient kernel implementations. Apart from SVMs and regression, SHOGUN also features a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons, and algorithms to train hidden Markov models. SHOGUN can be used from within C++, Matlab, R, Octave, and Python.
License: GNU General Public License (GPL)
Changes:
Shogun now fails nicely in “out of memory”
situations. The progress
output has been disabled by default. All
interfaces (including R)
are now installed via “configure; make; make
install”. The directory
structure has been revised, examples have been
ported to the R and
commandline interface, and the structure learning
branch has been
merged. Reference documentation for the static
interfaces is now
dynamically generated. A few crashers, memory
leaks, and compilation
problems have been fixed.