Joint Sub-classifiers One Class Classification Model For Avian Influenza Outbreak Detection

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dc.contributor.author Zhang, J
dc.contributor.author Lu, J
dc.contributor.author Zhang, G
dc.date.accessioned 2012-10-12T03:33:46Z
dc.date.issued 2011-01
dc.identifier.citation International Journal of Computational Intelligence and Applications, 2011, 10 (4), pp. 425 - 443
dc.identifier.issn 1469-0268
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/18280
dc.description.abstract H5N1 avian influenza outbreak detection is a significant issue for early warning of epidemics. This paper proposes domain knowledge-based joint one class classification model for avian influenza outbreak. Instead of focusing on manipulations of the one class classification model, we delve into the one class avian influenza dataset, divide it into subclasses by domain knowledge, train the sub-class classifiers and unify the result of each classifier. The proposed joint method solves the one class classification and features selection problems together. The experiment results demonstrate that the proposed joint model definitely outperforms the normal one class classification model on the animal avian influenza dataset.
dc.publisher Imperial College Press
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon 10.1142/S1469026811003173
dc.rights Electronic version of an article published as International Journal of Computational Intelligence and Applications Vol. 10, No. 4 (2011) 425–443 http://dx.doi.org/10.1142/S1469026811003173 © [copyright World Scientific Publishing Company] http://www.worldscientific.com/worldscinet/ijcia en_US
dc.title Joint Sub-classifiers One Class Classification Model For Avian Influenza Outbreak Detection
dc.type Journal Article
dc.parent International Journal of Computational Intelligence and Applications
dc.journal.volume 4
dc.journal.volume 10
dc.journal.number 4 en_US
dc.publocation United Kingdom en_US
dc.identifier.startpage 425 en_US
dc.identifier.endpage 443 en_US
dc.cauo.name FEIT.School of Software en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 001038
dc.personcode 020014
dc.personcode 105370
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 en_US
dc.description.keywords avian influenza; joint model; One class classification; outbreak detection en_US
dc.description.keywords avian influenza
dc.description.keywords joint model
dc.description.keywords One class classification
dc.description.keywords outbreak detection
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Strength - Quantum Computation and Intelligent Systems
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
utslib.collection.history Uncategorised (ID: 363)
utslib.collection.history General (ID: 2)


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