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A Multi-Class Support Vector Machine Based on Scatter Criteria
Robert Jenssen, Marius Kloft, Alexander Zien, Sören Sonnenburg and Klaus-Robert Müller
(2009)
Technical University Berlin, Berlin, Germany.
AbstractWe 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. [Edit]
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