Description:

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

o Different SVM formulations

o Efficient multi-class classification

o Cross validation for model selection

o Probability estimates

o Weighted SVM for unbalanced data

o Both C++ and Java sources

o GUI demonstrating SVM classification and regression

o 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.

o Automatic model selection which can generate contour of cross valiation accuracy.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Supported Operating Systems: Cygwin, Linux, Windows, Macos

Data Formats: None

Tags: Kernel, Svm, Classification, Regression, Support Vector Machines

Archive: download here

Other available revisons

Version	Changelog	Date
2.9	Initial Announcement on mloss.org.	February 27, 2010, 01:09:23
2.88	Initial Announcement on mloss.org.	November 13, 2007, 23:38:41

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