On K-means algorithm with the use of Mahalanobis distances

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dc.contributor.authorMelnykov, Igor
dc.contributor.authorMelnykov, Volodymyr
dc.creatorIgor, Melnykov
dc.date.accessioned2017-12-14T04:51:53Z
dc.date.available2017-12-14T04:51:53Z
dc.date.issued2014-01-01
dc.description.abstractAbstract The K-means algorithm is commonly used with the Euclidean metric. While the use of Mahalanobis distances seems to be a straightforward extension of the algorithm, the initial estimation of covariance matrices can be complicated. We propose a novel approach for initializing covariance matrices.en_US
dc.identifierDOI:10.1016/j.spl.2013.09.026
dc.identifier.citationIgor Melnykov, Volodymyr Melnykov, On K-means algorithm with the use of Mahalanobis distances, In Statistics & Probability Letters, Volume 84, 2014, Pages 88-95en_US
dc.identifier.issn01677152
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0167715213003246
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/2887
dc.language.isoenen_US
dc.publisherStatistics & Probability Lettersen_US
dc.relation.ispartofStatistics & Probability Letters
dc.rights.licenseCopyright © 2013 Elsevier B.V. All rights reserved.
dc.subjectK-means algorithmen_US
dc.subjectMahalanobis distanceen_US
dc.subjectInitializationen_US
dc.titleOn K-means algorithm with the use of Mahalanobis distancesen_US
dc.typeArticleen_US
elsevier.aggregationtypeJournal
elsevier.coverdate2014-01-01
elsevier.coverdisplaydateJanuary 2014
elsevier.endingpage95
elsevier.identifier.doi10.1016/j.spl.2013.09.026
elsevier.identifier.eid1-s2.0-S0167715213003246
elsevier.identifier.piiS0167-7152(13)00324-6
elsevier.identifier.scopusid84885983328
elsevier.openaccess0
elsevier.openaccessarticlefalse
elsevier.openarchivearticlefalse
elsevier.startingpage88
elsevier.teaserThe K-means algorithm is commonly used with the Euclidean metric. While the use of Mahalanobis distances seems to be a straightforward extension of the algorithm, the initial estimation of covariance...
elsevier.volume84
workflow.import.sourcescience

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