LIBSVM

Description

LIBSVM - A C/C++/Matlab/Java Library for Support Vector Machines LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.

Our goal is to help users from other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include:

• Different SVM formulations
• Efficient multi-class classification
• Cross validation for model selection
• Probability estimates
• Various kernels (including precomputed kernel matrix)
• Weighted SVM for unbalanced data
• Both C++ and Java sources
• GUI demonstrating SVM classification and regression
• Python, R, MATLAB, Perl, Ruby, Weka, Common LISP, CLISP, Haskell, and LabVIEW, interfaces. C# .NET code and CUDA extension is available.It's also included in some data mining environments: RapidMiner and PCP.
• Automatic model selection which can generate contour of cross valiation accuracy.

Copyright Remarks

Please cite the following document:

Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm

The bibtex format is:

@Manual{CC01a,
author = {Chih-Chung Chang and Chih-Jen Lin},
title = {{LIBSVM}: a library for support vector machines},
year = {2001},
note = {Software available at \url{http://www.csie.ntu.edu.tw/~cjlin/libsvm}}
}