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dc.contributor.authorTo, C
dc.contributor.authorNguyen, TT
dc.contributor.authorLiew, AWC
dc.contributor.editorX. Wang, W. Pedrycz, P. Chan, Q. He
dc.date.accessioned2018-03-28T01:30:37Z
dc.date.available2018-03-28T01:30:37Z
dc.date.issued2014
dc.identifier.isbn9783662456514
dc.identifier.issn1865-0929
dc.identifier.refurihttp://www.icmlc.com/ICMLC/formerICMLC_2014.html
dc.identifier.doi10.1007/978-3-662-45652-1_11
dc.identifier.urihttp://hdl.handle.net/10072/66985
dc.description.abstractIn pattern classification, when the feature space is of high dimension or patterns are "similar" on a subset of features only, the traditional clustering methods do not have good performances. Biclustering is a class of methods that simultaneously group on two dimensions and has many applications to different fields, especially gene expression data analysis. Because of simultaneous classification on both rows and columns of a data matrix, the biclustering problem is inherently intractable and computationally complex. and oOne of the most complex models in biclustering problem is linear coherent model. So sSeveral biclustering algorithms based on this model have been proposed in recent years. However, none of them is able to perfectly recognize all linear patterns in a bicluster. In this work, we propose a novel algorithm based on Hough transform that can find all linear coherent patterns and apply it to gene expression data.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.publisherSpringer
dc.publisher.placeGermany
dc.publisher.urihttp://www.icmlc.com/ICMLC/formerICMLC_2014.html
dc.relation.ispartofstudentpublicationY
dc.relation.ispartofconferencenameICMLC 2014
dc.relation.ispartofconferencetitleCommunications in Computer and Information Science
dc.relation.ispartofdatefrom2014-07-13
dc.relation.ispartofdateto2014-07-16
dc.relation.ispartoflocationLanzhou, China
dc.relation.ispartofpagefrom97
dc.relation.ispartofpageto106
dc.relation.ispartofvolume481
dc.rights.retentionY
dc.subject.fieldofresearchPattern Recognition and Data Mining
dc.subject.fieldofresearchcode080109
dc.titleA Hough Transform Based Biclustering Algorithm for Gene Expression Data
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionPost-print
gro.rights.copyright© 2014 Springer Berlin/Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com
gro.hasfulltextFull Text
gro.griffith.authorLiew, Alan Wee-Chung
gro.griffith.authorNguyen, Tien Thanh T.
gro.griffith.authorChieu To, Cuong


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