The conic-segmentation support vector machine - A target space method for multiclass classification Shilton, Alistair, Lai, Daniel T. H. and Palaniswami, M. 2012, The conic-segmentation support vector machine - A target space method for multiclass classification, in IJCNN 2012 : Proceedings of the International Joint Conference on Neural Networks, IEEE, Piscataway, N.J., doi: 10.1109/IJCNN.2012.6252441. Attached Files Name Description MIMEType Size Downloads Title The conic-segmentation support vector machine - A target space method for multiclass classification Author(s) Shilton, Alistair orcid.org/0000-0002-0849-3271 Lai, Daniel T. H. Palaniswami, M. Conference name IJCNN - Neural Networks. International Joint Conference (2012 : Brisbane, Queensland) Conference location Brisbane, Queensland Conference dates 10 - 15 Jun. 2012 Title of proceedings IJCNN 2012 : Proceedings of the International Joint Conference on Neural Networks Publication date 2012 Total pages 8 Publisher IEEE Place of publication Piscataway, N.J. Keyword(s) training support vector machines vectors zinc kernel standards encoding ISBN 9781467314909 ISSN 2161-4393 2161-4407 Language eng DOI 10.1109/IJCNN.2012.6252441 Indigenous content off HERDC Research category E1.1 Full written paper - refereed Copyright notice ©2012, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30124636 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment Centre for Pattern Recognition and Data Analytics (PRADA) Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Wed, 03 Jul 2019, 15:44:39 EST Thu, 04 Jul 2019, 05:03:33 EST Thu, 19 Nov 2020, 06:34:05 EST Thu, 19 Nov 2020, 06:36:32 EST Thu, 19 Nov 2020, 06:46:13 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 36 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Wed, 03 Jul 2019, 15:44:39 EST

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