The Algorithm Design Manual
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Programming Challenges

The Stony Brook Algorithm Repository

Steven Skiena
Stony Brook University
Dept. of Computer Science

LIBSVM -- A 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 * Weighted SVM for unbalanced data * Both C++ and Java sources * GUI demonstrating SVM classification and regression * Python, R (also Splus), MATLAB, Perl, Ruby, Weka, CLISP and LabVIEW interfaces. C# .NET code is available. It's also included in some learning environments: YALE and PCP. * Automatic model selection which can generate contour of cross valiation accuracy.

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    This page last modified on 2008-07-10 .