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dc.contributor.authorNg, SK
dc.contributor.authorMcLachlan, GJ
dc.contributor.editorZhang, S
dc.contributor.editorJarvis, R
dc.date.accessioned2017-05-03T15:26:13Z
dc.date.available2017-05-03T15:26:13Z
dc.date.issued2005
dc.date.modified2011-06-30T08:41:30Z
dc.identifier.issn0302-9743
dc.identifier.doi10.1007/11589990_101
dc.identifier.urihttp://hdl.handle.net/10072/39323
dc.description.abstractWith mixed feature data, problems are induced in modeling the gating network of normalized Gaussian (NG) networks as the assumption of multivariate Gaussian becomes invalid. In this paper, we propose an independence model to handle mixed feature data within the framework of NG networks. The method is illustrated using a real example of breast cancer data.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.publisher.placeBerlin
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom879
dc.relation.ispartofpageto882
dc.relation.ispartofjournalLecture Notes in Artificial Intelligence
dc.relation.ispartofvolume3809
dc.rights.retentionY
dc.subject.fieldofresearchcode230204
dc.titleNormalized Gaussian networks with mixed feature data
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.date.issued2005
gro.hasfulltextNo Full Text
gro.griffith.authorNg, Shu Kay Angus


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