LIBSVM
| Domain | Machine Learning |
| Media | |
| Task | |
| Creation Date | |
| Copyright | cite paper - see below |
| URL | http://www.csie.ntu.edu.tw/~cjlin/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}}
}
