Show simple item record

dc.contributor.authorGurrutxaga Goikoetxea, Ibai ORCID
dc.contributor.authorMuguerza Rivero, Javier Francisco ORCID
dc.contributor.authorArbelaiz Gallego, Olatz ORCID
dc.contributor.authorPérez, Jesús M.
dc.contributor.authorMartín, José I.
dc.date.accessioned2015-11-19T16:11:17Z
dc.date.available2015-11-19T16:11:17Z
dc.date.issued2011-02-01
dc.identifier.citationPattern Recognition Letters, Vol. 32 (3) pp. 505-515es
dc.identifier.issn0167-8655
dc.identifier.urihttp://hdl.handle.net/10810/16126
dc.description.abstractThe evaluation and comparison of internal cluster validity indices is a critical problem in the clustering area. The methodology used in most of the evaluations assumes that the clustering algorithms work correctly. We propose an alternative methodology that does not make this often false assumption. We compared 7 internal cluster validity indices with both methodologies and concluded that the results obtained with the proposed methodology are more representative of the actual capabilities of the compared indices.es
dc.language.isoenges
dc.publisherElsevieres
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectcluster validationes
dc.subjectcluster validity indexes
dc.subjectunsupervised learninges
dc.titleTowards a standard methodology to evaluate internal cluster validity indiceses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holderCopyright © 2015 Elsevier B.V.es
dc.relation.publisherversionhttp://www.journals.elsevier.com/pattern-recognition-letters/es
dc.identifier.doi10.1016/J.PATREC.2010.11.006
dc.departamentoesArquitectura y Tecnología de Computadoreses_ES
dc.departamentoeuKonputagailuen Arkitektura eta Teknologiaes_ES
dc.subject.categoriaCOMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
dc.subject.categoriaSOFTWARE
dc.subject.categoriaSIGNAL PROCESSING
dc.subject.categoriaCOMPUTER VISION AND PATTERN RECOGNITION


Files in this item

Thumbnail
Thumbnail
Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record

Copyright © 2015 Elsevier B.V.
Except where otherwise noted, this item's license is described as Copyright © 2015 Elsevier B.V.