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Support Vector Machines and other kernel-based learning methods

John Shawe-Taylor & Nello Cristianini - Cambridge University Press, 2000 - Ordering Info »

Software

Pointers to Support Vector Machine and Gaussian Processes Software

http://www.cs.ucl.ac.uk/staff/M.Sewell/winsvm/
http://www.cs.ucl.ac.uk/staff/M.Sewell/svmdark/
SVM MATLAB TOOLBOX from Graz
SVM & KM matlab toolbox, from Insa de Rouen
GPDT parallel software for SVMs from University of Ferrara and University of Modena, Italy
Gist: software for support vector machine classification and for kernel principal components analysis.
Matlab Interface: a MATLAB interface to SVMlight written by Anton Schwaighofer (for SVM^light V4.00)
jSVM: a JAVA interface to SVM^light written by Heloise Hwawen Hse (for SVM^light V2.01)
A special version of SVM^light is integrated into the virtual file system libferris by Ben Martin
A WINDOWS implementation by Chen Longbin
Collobert and Bengio's Torch
Stefan Ruping's mySVM for Windows and Unix
Java Implementation of LIBSVM
Chih-Jen Lin looms
Musicant's lagrangian Support Vector Machine
Musicant's ASVM
MATLAB Support Vector Machine Toolbox by Gavin Cawley
SVMTorch by Collobert and Bengio, extends ideas from SVMlight
NodeLib by Flake and Lawrence contains a SVM package related to SMO
BSVM - by Chih-Wei Hsu and Chih-Jen Lin, (also in Windows version). See also LIBSVM by the same authors.
SVM code implemented by prof. Keerthi (Nearest Point algorithm) in fortran.
Code for SMO implemented by Xianping Ge can be obtained from this site.
The implementation of Support Vector Machines jointly developed by C. Saunders, M. O. Stitson, J. Weston, L. Bottou, B. Schölkopf and A. Smola at Royal Holloway, AT&T and GMD-FIRST is available here with its reference manual.
Thorsten Joachims' implementation of Support Vector Machine, SVM light.
Matlab implementation by Steve Gunn, MATLAB SVM toolbox.
SVM Fu (Support Vector Machine code by Ryan Rifkin).
SMOBR
Rupings's mySVM
The "Tpros" and "Cpros" packages for Gaussian Processes written by Mark N. Gibbs are available at this page.
Radford M. Neal's package Software for flexible Bayesian modeling, includes programs for neural networks, Gaussian processes and mixture models.
The gp-map-1 and gp-mc-1 programs for Gaussian Processes written by Carl Edward Rasmussen are available through the DELVE web-site.
A demonstration of Gaussian Processes written in 'octave' by David J. C. MacKay is also available.
Quadratic Programming packages: R. Vanderbei's LOQO interior point optimizer and
Alex Smola's Quadratic Optimizer for SV Pattern Recognition based on the Interior Point Algorithm.

More Software

KernLab, R library for Kernel Methods
Gist: software for support vector machine classification and for kernel principal components analysis.
Thorsten Joachims' implementation of Support Vector Machine, SVM light.
Matlab implementation by Steve Gunn, MATLAB SVM toolbox.
SVM & KM matlab toolbox, from Insa de Rouen (totally in MATLAB)