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Improved pseudoinverse linear discriminant analysis method for dimensionality reduction

dc.contributor.authorPaliwal, Kuldip K
dc.contributor.authorSharma, Alok
dc.date.accessioned2017-05-03T13:01:19Z
dc.date.available2017-05-03T13:01:19Z
dc.date.issued2012
dc.date.modified2013-03-27T23:22:59Z
dc.identifier.issn0218-0014
dc.identifier.doi10.1142/S0218001412500024
dc.identifier.urihttp://hdl.handle.net/10072/50042
dc.description.abstractPseudoinverse linear discriminant analysis (PLDA) is a classical method for solving small sample size problem. However, its performance is limited. In this paper, we propose an improved PLDA method which is faster and produces better classification accuracy when experimented on several datasets.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherWorld Scientific Publishing
dc.publisher.placeSingapore
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom1250002-1
dc.relation.ispartofpageto1250002-9
dc.relation.ispartofissue1
dc.relation.ispartofjournalInternational Journal of Pattern Recognition and Artificial Intelligence
dc.relation.ispartofvolume26
dc.rights.retentionY
dc.subject.fieldofresearchCognitive and computational psychology
dc.subject.fieldofresearchcode5204
dc.titleImproved pseudoinverse linear discriminant analysis method for dimensionality reduction
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.date.issued2012
gro.hasfulltextNo Full Text
gro.griffith.authorPaliwal, Kuldip K.


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