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EnsembleSVM : A library for ensemble learning using support vector machines

Journal Contribution - Journal Article

EnsembleSVM is a free software package containing effcient routines to perform ensemble learning with support vector machine (SVM) base models. It currently offers ensemble methods based on binary SVM models. Our implementation avoids duplicate storage and evaluation of support vectors which are shared between constituent models. Experimental results show that using ensemble approaches can drastically reduce training complexity while maintaining high predictive accuracy. The EnsembleSVM software package is freely available online at http://esat.kuleuven.be/stadius/ensemblesvm. © 2014 Marc Claesen, Frank De Smet, Johan A.K. Suykens and Bart De Moor.
Journal: JMLR Workshop and Conference Proceedings
ISSN: 1532-4435
Volume: 15
Pages: 141 - 145
Publication year:2014
BOF-keylabel:yes
IOF-keylabel:yes
BOF-publication weight:2
CSS-citation score:2
Authors from:Higher Education
Accessibility:Open