Fast Linear binary SVM classifier

Fast implementation of Linear binary SVM via BLAS/OpenMP API
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Updated 29 Jan 2020

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LSVM v 3.0
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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 [1] and LIBLINEAR [2].

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 [2] 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

Installation
------------

Run "mexme_lsvm.m" to compile mex-files.

Testing
-------

Run "test_lsvm.m" for demo

Online help by typing pegasos_train or cddcsvm_train in matlab prompt.

References :
----------
[1] S. Shalev-Shwartz, Y. Singer, and N. Srebro. "Pegasos: Primal estimated sub-GrAdient SOlver for SVM."
In Proc. ICML, 2007.
[2] Liblinear: http://www.csie.ntu.edu.tw/~cjlin/liblinear/

Cite As

Sebastien PARIS (2024). Fast Linear binary SVM classifier (https://www.mathworks.com/matlabcentral/fileexchange/33621-fast-linear-binary-svm-classifier), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2018b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.3.0.0

Fixed bugs & compatible with modern Matlab & OS64

1.2.0.0

- Fix a bug for single precision
- Fix a crash for large-scale data with OS64

1.1.0.0

-Cosmetic changes

1.0.0.0