Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-10264
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Main Title: A Multi-Class Support Vector Machine Based on Scatter Criteria
Author(s): Jenssen, Robert
Kloft, Marius
Zien, Alexander
Sonnenburg, Sören
Müller, Klaus-Robert
Type: Research Paper
Language Code: en
Abstract: We re-visit Support Vector Machines (SVMs) and provide a novel interpretation thereof in terms of weighted class means and scatter theory. The gained theoretical insight can be translated into a highly efficient extension to multi-class SVMs: mScatter-SVMs. Numerical simulations reveal that more than an order of magnitude speed-up can be gained while the classification performance remains largely unchanged at the level of the classical one vs. rest and one vs. one implementation of multi-class SVMs.
URI: https://depositonce.tu-berlin.de/handle/11303/11377
http://dx.doi.org/10.14279/depositonce-10264
Issue Date: 2009
Date Available: 15-Jun-2020
DDC Class: 004 Datenverarbeitung; Informatik
Subject(s): support vector machines
mScatter-SVM
License: http://rightsstatements.org/vocab/InC/1.0/
Series: Forschungsberichte der Fakultät IV - Elektrotechnik und Informatik / Technische Universität Berlin
Series Number: 2009-14
ISSN: 1436-9915
Appears in Collections:Fak. 4 Elektrotechnik und Informatik » Publications

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