Une boîte à outils rapide et simple pour les SVM
Gaëlle Loosli, Stéphane Canu, S V N Vishwanathan, Alex Smola and Manojit Chattopadhyay
If SVM (Support Vector Machines) is now considered as one of the best learning methods, it is still considered as slow.
Here we propose a Matlab toolbox that enables the usage of SVM in a fast and simple way. This is done thanks to the projected gradient method which is well adapted to the problem: SimpleSVM
We implement this algorithm with Matlab environment since it is user-friendly and efficient.
The comparison between our solution and the state of the art in this domain SMO (Sequential Minimal Optimization) shows that in some case this solution is faster and has a lower complexity.
|Additional Information:||The paper was published in french, however the english version is also available.|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Subjects:||Learning/Statistics & Optimisation|
|Deposited By:||Gaëlle Loosli|
|Deposited On:||23 November 2004|