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Cluster number selection for a small set of samples using the Bayesian Ying-Yang model
Guo P.1; Chen C.L.P.2; Lyu M.R.3
2002-05-01
Source PublicationIEEE Transactions on Neural Networks
ISSN10459227
Volume13Issue:3Pages:757-763
AbstractOne major problem in duster analysis is the determination of the number of clusters. In this paper, we describe both theoretical and experimental results in determining the cluster number for a small set of samples using the Bayesian-Kull-back Ying-Yang (BYY) model selection criterion. Under the second-order approximation, we derive a new equation for estimating the smoothing parameter in the cost function. Finally, we propose a gradient descent smoothing parameter estimation approach that avoids complicated integration procedure and gives the same optimal result.
KeywordBootstrap Cluster number selection Data smoothing SEM algorithm Small number sample set Smoothing parameter estimation
DOI10.1109/TNN.2002.1000144
URLView the original
Language英語English
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Cited Times [WOS]:58   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Beijing Normal University
2.Wright State University
3.Chinese University of Hong Kong
Recommended Citation
GB/T 7714
Guo P.,Chen C.L.P.,Lyu M.R.. Cluster number selection for a small set of samples using the Bayesian Ying-Yang model[J]. IEEE Transactions on Neural Networks,2002,13(3):757-763.
APA Guo P.,Chen C.L.P.,&Lyu M.R..(2002).Cluster number selection for a small set of samples using the Bayesian Ying-Yang model.IEEE Transactions on Neural Networks,13(3),757-763.
MLA Guo P.,et al."Cluster number selection for a small set of samples using the Bayesian Ying-Yang model".IEEE Transactions on Neural Networks 13.3(2002):757-763.
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