A Multi-SVM Classification System

Frossyniotis, D; Stafylopatis, A

dc.contributor.author	Frossyniotis, D	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T02:49:02Z
dc.date.available	2014-03-01T02:49:02Z
dc.date.issued	2001	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34239
dc.subject	Classification System	en
dc.subject	Classifier System	en
dc.subject	Divide and Conquer	en
dc.subject	Fuzzy C Mean	en
dc.subject	Support Vector Machine	en
dc.subject	Unsupervised Learning	en
dc.title	A Multi-SVM Classification System	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/3-540-48219-9_20	en
heal.identifier.secondary	http://dx.doi.org/10.1007/3-540-48219-9_20	en
heal.publicationDate	2001	en
heal.abstract	It has been shown by several researchers that multi-classifier systems can result in effective solutions to difficult tasks. In this work, we propose a multi-classifier system based on both supervised and unsupervised learning. According to the principle of “divide-and-conquer”, the input space is partitioned into overlapping subspaces and Support Vector Machines (SVMs) are subsequently used to solve the respective classification	en
heal.journalName	Multiple Classifier Systems	en
dc.identifier.doi	10.1007/3-540-48219-9_20	en