Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/25842
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dc.contributor.authorAkogul, Serkan-
dc.contributor.authorErisoglu, Murat-
dc.date.accessioned2019-09-09T08:31:56Z-
dc.date.available2019-09-09T08:31:56Z-
dc.date.issued2017-08-29-
dc.identifier.issn1099-4300-
dc.identifier.urihttps://hdl.handle.net/11499/25842-
dc.identifier.urihttps://doi.org/10.3390/e19090452-
dc.description.abstractTo determine the number of clusters in the clustering analysis that has a broad range of applied sciences, such as physics, chemistry, biology, engineering, economics etc., many methods have been proposed in the literature. The aim of this paper is to determine the number of clusters of a dataset in a model-based clustering by using an Analytic Hierarchy Process (AHP). In this study, the AHP model has been created by using the information criteria Akaike’s Information Criterion (AIC), Approximate Weight of Evidence (AWE), Bayesian Information Criterion (BIC), Classification Likelihood Criterion (CLC), and Kullback Information Criterion (KIC). The achievement of the proposed approach has been tested on common real and synthetic datasets. The proposed approach based on the corresponding information criteria has produced accurate results. The currently producen_US
dc.language.isoenen_US
dc.relation.ispartofEntropyen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectmodel-based clusteringen_US
dc.subjectinformation criteriaen_US
dc.subjectcluster analysisen_US
dc.subjectanalytic hierarchy processen_US
dc.titleAn approach for determining the number of clusters in a model-based cluster analysisen_US
dc.typeArticleen_US
dc.identifier.volume19en_US
dc.identifier.issue452en_US
dc.authorid0000-0002-0346-4308-
dc.identifier.doi10.3390/e19090452-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.wosWOS:000411527100024en_US
dc.identifier.scopusqualityQ2-
dc.ownerPamukkale University-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.fulltextWith Fulltext-
crisitem.author.dept17.07. Statistics-
Appears in Collections:Fen-Edebiyat Fakültesi Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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