Fast Linear binary SVM classifier

Fast implementation of Linear binary SVM via BLAS/OpenMP API
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Mise à jour 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
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Run "mexme_lsvm.m" to compile mex-files.

Testing
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Run "test_lsvm.m" for demo

Online help by typing pegasos_train or cddcsvm_train in matlab prompt.

References :
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[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/

Citation pour cette source

Sebastien PARIS (2026). Fast Linear binary SVM classifier (https://fr.mathworks.com/matlabcentral/fileexchange/33621-fast-linear-binary-svm-classifier), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2018b
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux
Catégories
En savoir plus sur Classification dans Help Center et MATLAB Answers
Version Publié le Notes de version
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