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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. The basic algorithm
is a simplification of both SMO by Platt and SVMLight by Joachims. It is also
a simplification of the modification 2 of SMO by Keerthi et al.
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
Weighted SVM for unbalanced data
Both C++ and Java sources
GUI demonstrating SVM classification and regression
WWW: http://www.csie.ntu.edu.tw/~cjlin/libsvm/
Author: Chih-Chung Chang and Chih-Jen Lin <cjlin@csie.ntu.edu.tw>
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