A Multi-Class Support Vector Machine Based on Scatter Criteria

Jenssen, RobertKloft, MariusZien, AlexanderSonnenburg, SörenMüller, Klaus-Robert2020-06-152020-06-1520091436-9915https://depositonce.tu-berlin.de/handle/11303/11377http://dx.doi.org/10.14279/depositonce-10264We 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.en004 Datenverarbeitung; Informatiksupport vector machinesmScatter-SVMA Multi-Class Support Vector Machine Based on Scatter CriteriaResearch Paper