Dark Patches in Clustering

dc.contributor.authorIshaq, Waqar
dc.contributor.authorBüyükkaya, Eliya
dc.date.accessioned2019-06-27T08:01:26Z
dc.date.available2019-06-27T08:01:26Z
dc.date.issued2017
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractThis survey highlights issues in clustering which hinder in achieving optimal solution or generates inconsistent outputs. We called such malignancies as dark patches. We focus on the issues relating to clustering rather than concepts and techniques of clustering. For better insight into the issues of clustering we categorize dark patches into three classes and then compare various clustering methods to analyze distributed datasets with respect to classes of dark patches rather than conventional way of comparison by performance and accuracy criteria because performance and accuracy may provide misleading conclusions due to lack of labeled data in unsupervised learning. To the best of our knowledge this prime feature makes our survey paper unique from other clustering survey papers.en_US]
dc.identifier.citation1
dc.identifier.endpage811
dc.identifier.isbn978-1-5386-0930-9
dc.identifier.scopus2-s2.0-85040571112en_US
dc.identifier.startpage806en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/381
dc.identifier.wosWOS:000426856900151en_US
dc.institutionauthorIshaq, Waqaren_US
dc.institutionauthorBüyükkaya, Eliya
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.journal2017 International Conference on Computer Science and Engineering (UBMK)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClustering issuesen_US
dc.subjectTaxonomy of clustering methods and modelen_US
dc.subjectClustering surveyen_US
dc.titleDark Patches in Clusteringen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
relation.isAuthorOfPublicationfbc6008d-9797-4687-8f0a-43c963272c4a
relation.isAuthorOfPublication.latestForDiscoveryfbc6008d-9797-4687-8f0a-43c963272c4a

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