Online updating of active function cross-entropy clustering

2019
journal article
article
2
cris.lastimport.wos2024-04-09T22:22:31Z
dc.abstract.enGaussian mixture models have many applications in density estimation and data clustering. However, the model does not adapt well to curved and strongly nonlinear data, since many Gaussian components are typically needed to appropriately fit the data that lie around the nonlinear manifold. To solve this problem, the active function cross-entropy clustering (afCEC) method was constructed. In this article, we present an online afCEC algorithm. Thanks to this modification, we obtain a method which is able to remove unnecessary clusters very fast and, consequently, we obtain lower computational complexity. Moreover, we obtain a better minimum (with a lower value of the cost function). The modification allows to process data streams.pl
dc.affiliationWydział Matematyki i Informatyki : Instytut Informatyki i Matematyki Komputerowejpl
dc.contributor.authorSpurek, Przemysław - 135993 pl
dc.contributor.authorByrski, Krzysztof - 176317 pl
dc.contributor.authorTabor, Jacek - 132362 pl
dc.date.accessioned2019-11-22T13:41:28Z
dc.date.available2019-11-22T13:41:28Z
dc.date.issued2019pl
dc.date.openaccess0
dc.description.accesstimew momencie opublikowania
dc.description.number4pl
dc.description.physical1409-1425pl
dc.description.versionostateczna wersja wydawcy
dc.description.volume22pl
dc.identifier.doi10.1007/s10044-018-0701-8pl
dc.identifier.eissn1433-755Xpl
dc.identifier.issn1433-7541pl
dc.identifier.project2015/19/D/ST6/01472pl
dc.identifier.project2017/25/B/ST6/01271pl
dc.identifier.projectROD UJ / OPpl
dc.identifier.urihttps://ruj.uj.edu.pl/xmlui/handle/item/87740
dc.languageengpl
dc.language.containerengpl
dc.rightsUdzielam licencji. Uznanie autorstwa 4.0 Międzynarodowa*
dc.rights.licenceCC-BY
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/legalcode.pl*
dc.share.typeinne
dc.subject.enclusteringpl
dc.subject.enactive function cross-entropy clusteringpl
dc.subject.enGaussian mixture modelspl
dc.subject.endata streamspl
dc.subtypeArticlepl
dc.titleOnline updating of active function cross-entropy clusteringpl
dc.title.journalPattern Analysis and Applicationspl
dc.typeJournalArticlepl
dspace.entity.typePublication
cris.lastimport.wos
2024-04-09T22:22:31Z
dc.abstract.enpl
Gaussian mixture models have many applications in density estimation and data clustering. However, the model does not adapt well to curved and strongly nonlinear data, since many Gaussian components are typically needed to appropriately fit the data that lie around the nonlinear manifold. To solve this problem, the active function cross-entropy clustering (afCEC) method was constructed. In this article, we present an online afCEC algorithm. Thanks to this modification, we obtain a method which is able to remove unnecessary clusters very fast and, consequently, we obtain lower computational complexity. Moreover, we obtain a better minimum (with a lower value of the cost function). The modification allows to process data streams.
dc.affiliationpl
Wydział Matematyki i Informatyki : Instytut Informatyki i Matematyki Komputerowej
dc.contributor.authorpl
Spurek, Przemysław - 135993
dc.contributor.authorpl
Byrski, Krzysztof - 176317
dc.contributor.authorpl
Tabor, Jacek - 132362
dc.date.accessioned
2019-11-22T13:41:28Z
dc.date.available
2019-11-22T13:41:28Z
dc.date.issuedpl
2019
dc.date.openaccess
0
dc.description.accesstime
w momencie opublikowania
dc.description.numberpl
4
dc.description.physicalpl
1409-1425
dc.description.version
ostateczna wersja wydawcy
dc.description.volumepl
22
dc.identifier.doipl
10.1007/s10044-018-0701-8
dc.identifier.eissnpl
1433-755X
dc.identifier.issnpl
1433-7541
dc.identifier.projectpl
2015/19/D/ST6/01472
dc.identifier.projectpl
2017/25/B/ST6/01271
dc.identifier.projectpl
ROD UJ / OP
dc.identifier.uri
https://ruj.uj.edu.pl/xmlui/handle/item/87740
dc.languagepl
eng
dc.language.containerpl
eng
dc.rights*
Udzielam licencji. Uznanie autorstwa 4.0 Międzynarodowa
dc.rights.licence
CC-BY
dc.rights.uri*
http://creativecommons.org/licenses/by/4.0/legalcode.pl
dc.share.type
inne
dc.subject.enpl
clustering
dc.subject.enpl
active function cross-entropy clustering
dc.subject.enpl
Gaussian mixture models
dc.subject.enpl
data streams
dc.subtypepl
Article
dc.titlepl
Online updating of active function cross-entropy clustering
dc.title.journalpl
Pattern Analysis and Applications
dc.typepl
JournalArticle
dspace.entity.type
Publication
Affiliations

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