Nesting One-Against-One Algorithm Based on SVMs for Pattern Classification

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dc.contributor.author Liu, B
dc.contributor.author Hao, Z
dc.contributor.author Tsang, EC
dc.date.accessioned 2012-02-02T09:46:04Z
dc.date.issued 2008-01
dc.identifier.citation IEEE Transactions On Neural Networks, 2008, 19 (12), pp. 2044 - 2052
dc.identifier.issn 1045-9227
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/15153
dc.description.abstract Support vector machines (SVMs), which were originally designed for binary classifications, are an excellent tool for machine learning. For the multiclass classifications, they are usually converted into binary ones before they can be used to classify the
dc.publisher IEEE-Inst Electrical Electronics Engineers Inc
dc.relation.isbasedon 10.1109/TNN.2008.2003298
dc.title Nesting One-Against-One Algorithm Based on SVMs for Pattern Classification
dc.type Journal Article
dc.parent IEEE Transactions On Neural Networks
dc.journal.volume 12
dc.journal.volume 19
dc.journal.number 12 en_US
dc.publocation Piscataway, USA en_US
dc.identifier.startpage 2044 en_US
dc.identifier.endpage 2052 en_US
dc.cauo.name SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 100970
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity ISI:000261544900005 en_US
dc.description.keywords Support Vector Machines; Multiclass Classification en_US
dc.description.keywords Support Vector Machines
dc.description.keywords Multiclass Classification
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10


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