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dc.contributor.authorGümüş, H.
dc.contributor.authorKorkmaz Özay, E.
dc.contributor.authorArı, İsmail
dc.contributor.authorÇataltepe, Z.
dc.date.accessioned2016-02-11T06:46:13Z
dc.date.available2016-02-11T06:46:13Z
dc.date.issued2012
dc.identifier.isbn978-1-4673-0055-1
dc.identifier.urihttp://hdl.handle.net/10679/1958
dc.identifier.urihttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6204721
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractClustering is a common technique, in all areas where information is obtained from the collected data. In this work, three well-known clustering algorithms namely, K-means, Spectral and DBSCAN are investigated in terms of their validity using four clustering validity indexes, Rand, Adjusted Rand, Jaccard, Silhouette. These clustering algorithms are applied on three data sets which have different characteristics. Thus steps have been taken for an automated clustering optimization system.
dc.description.sponsorshipTÜBİTAK ; European Commission
dc.language.isotur
dc.publisherIEEE
dc.relationinfo:turkey/grantAgreement/TUBITAK/190E194
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/256537
dc.relation.ispartof2012 20th Signal Processing and Communications Applications Conference (SIU)
dc.rightsrestrictedAccess
dc.titleÖbekleme eniyilemesi ve sağlamlığı için yinelemeli bir yaklaşımen_US
dc.title.alternativeAn iterative approach for clustering optimization and validation
dc.typeConference paperen_US
dc.peerreviewedyes
dc.publicationstatuspublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0002-6159-0484 & YÖK ID 43541) Arı, İsmail
dc.contributor.ozuauthorArı, İsmail
dc.identifier.startpage1
dc.identifier.endpage4
dc.identifier.doi10.1109/SIU.2012.6204721
dc.subject.keywordsIterative methods
dc.subject.keywordsPattern clustering
dc.identifier.scopusSCOPUS:2-s2.0-84863433940
dc.contributor.authorMale1
dc.relation.publicationcategoryConference Paper - International - Institutional Academic Staff


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