A library for supporting vector machines
LIBSVM is an integrated component designed to support vector classification, (C-SVC, nu-SVC), distribution estimation (one-class SVM) and regression (epsilon-SVR, nu-SVR). It supports multi-class classification.
- 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, Common LISP, CLISP, Haskell and LabVIEW interfaces. C# .NET code 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.
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