LSVM v 3.0
Fast Linear SVM binary solver toolbox such PEGASOS/LIBLINEAR.
This toolbox offers fast implementation via mex-files of the two most
popular Linear SVM algorithms for binary classification: PEGASOS  and LIBLINEAR .
This toolbox can use BLAS/OpenMP API for faster computation on multi-cores processor.
It accepts dense inputs in single/double precision.
For comparaison with  in binary case, this package requires less memory and is approximatively between 10% up to 50% faster. Ideal for Large-scale training in computer vision for example
Run "mexme_lsvm.m" to compile mex-files.
Run "test_lsvm.m" for demo
Online help by typing pegasos_train or cddcsvm_train in matlab prompt.
 S. Shalev-Shwartz, Y. Singer, and N. Srebro. "Pegasos: Primal estimated sub-GrAdient SOlver for SVM."
In Proc. ICML, 2007.
 Liblinear: http://www.csie.ntu.edu.tw/~cjlin/liblinear/
Sebastien PARIS (2020). Fast Linear binary SVM classifier (https://www.mathworks.com/matlabcentral/fileexchange/33621-fast-linear-binary-svm-classifier), MATLAB Central File Exchange. Retrieved .
Venkat .... optimize your C be cross-validation
Thank you for sharing excellent software.
I am having training data of orders 9500 x 200000. Can you suggest some tips, if any on choice of algorithm/parameters.
I found cddcsvm_train, with C =5, B =1; better than PEGASOS.
But didn't know if any other choice of parameters-C or optimization technique can yield better results.
Sebastien, thanks for sharing such a great toolbox!
Fixed bugs & compatible with modern Matlab & OS64
- Fix a bug for single precision