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dc.contributor.authorFieldsend, Jonathan E.
dc.contributor.authorEverson, Richard M.
dc.date.accessioned2013-07-08T15:25:18Z
dc.date.issued2007-11-15
dc.description.abstractThis chapter sets out a number of the popular areas in multiobjective supervised learning. It gives empirical examples of model complexity optimization and competing error terms, and presents the recent advances in multi-class receiver operating characteristic analysis enabled by multiobjective optimization. It concludes by highlighting some specific areas of interest/concern when dealing with multiobjective supervised learning problems, and sets out future areas of potential research.en_GB
dc.identifier.citationIn: Multiobjective Problem Solving from Nature - From Concepts to Applications, edited by Joshua Knowles, David Corne, and Kalyanmoy Deb, pp. 155 - 176en_GB
dc.identifier.doi10.1007/978-3-540-72964-8_8
dc.identifier.urihttp://hdl.handle.net/10871/11569
dc.language.isoenen_GB
dc.publisherSpringeren_GB
dc.relation.isversionofhttp://hdl.handle.net/10871/11785
dc.relation.urlhttp://hdl.handle.net/10871/11785
dc.titleMulti-Objective Supervised Learning (book chapter)en_GB
dc.typeBook chapteren_GB
dc.date.available2013-07-08T15:25:18Z
dc.identifier.isbn9783540729631
dc.identifier.isbn9783540729648
dc.identifier.issn1619-7127
dc.descriptionCopyright © 2008 Springer-Verlag Berlin Heidelberg. The final publication is available at link.springer.comen_GB
dc.descriptionExtended version of the 2006 workshop paper presented at the Workshop on Multiobjective Problem-Solving from Nature, 9th International Conference on Parallel Problem Solving from Nature (PPSN IX), Reykjavik, Iceland, 9-13 September 2006; see: http://hdl.handle.net/10871/11785


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