This tool provides a simple interface to LIBSVM, a library for support vector
It is very easy to use as
the usage and the way of specifying parameters are the same as that of LIBSVM.
This tool provides also a simple interface to LIBLINEAR, a library for
large-scale regularized linear classification (http://www.csie.ntu.edu.tw/~cjlin/liblinear).
It is very easy to use as the usage and the way of specifying parameters are
the same as that of LIBLINEAR.
This Toolbox is compatible with the NaN-toolbox!
- buxfix for getpath
- help files fixed for libsvm_linpredict and libsvm_lintrain
- path operations are replaced by fullfile
- unit tests for libsvmwrite and libsvmread
- fix issues 805, 806, 808, 809, 813, 814,
- renaming of the following functions:
*svmtrain > libsvm_svmtrain
*svmpredict > libsvm_svmpredict
*train > libsvm_lintrain
*predict > libsvm_linpredict
*svmconfmat > libsvm_confmat
*svmgrid > libsvm_grid
*svmgridlinear > libsvm_gridlinear
*svmnormalize > libsvm_normalize
*svmpartest > libsvm_partest
*svmrocplot > libsvm_rocplot
*svmscale > libsvm_scale
*svmtoy > libsvm_toy
- compatible with scilab-5.4.0-beta-1 and scilab-5.4.0-alpha-1 or lower
- compatible with scilab-5.4.0-beta-1
- incompatible with scilab-5.4.0-alpha-1 and lower
- fix several bugs in examples
- fix precomputed kernel bug in svmtrain
- LIBLINEAR is updated to 1.91
- LIBSVM is updated to 3.12
- some bug fixes
- help files improved
- svmtoy added
- improved error handling in sci_gateway
- improved help files
- bug in performance demo removed
- the Nan-Toolbox 1.3 is compatible to this toolbox now!
- improved help-files
- improved demos
- LIBLINEAR with optional instance weight support
- improved demos
- works under Windows
- new function: svmnormalize
- first release of libsvm - toolbox
This interface was initially written by Jun-Cheng Chen, Kuan-Jen Peng,
Chih-Yuan Yang and Chih-Huai Cheng from Department of Computer
Science, National Taiwan University.
It was converted to Scilab 5.3 by Holger Nahrstaedt from TU Berlin.
If you find this tool useful, please cite LIBSVM as follows
Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support
vector machines. ACM Transactions on Intelligent Systems and
Technology, 2:27:1--27:27, 2011. Software available at
Please cite LIBLINEAR as follows
R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin.
LIBLINEAR: A Library for Large Linear Classification, Journal of
Machine Learning Research 9(2008), 1871-1874.Software available at