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dc.contributor.authorHämäläinen, Joonas
dc.contributor.authorJauhiainen, Susanne
dc.contributor.authorKärkkäinen, Tommi
dc.date.accessioned2017-11-22T10:54:22Z
dc.date.available2017-11-22T10:54:22Z
dc.date.issued2017
dc.identifier.citationHämäläinen, J., Jauhiainen, S., & Kärkkäinen, T. (2017). Comparison of Internal Clustering Validation Indices for Prototype-Based Clustering. <i>Algorithms</i>, <i>10</i>(3), Article 105. <a href="https://doi.org/10.3390/a10030105" target="_blank">https://doi.org/10.3390/a10030105</a>
dc.identifier.otherCONVID_27369288
dc.identifier.otherTUTKAID_75786
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/55978
dc.description.abstractClustering is an unsupervised machine learning and pattern recognition method. In general, in addition to revealing hidden groups of similar observations and clusters, their number needs to be determined. Internal clustering validation indices estimate this number without any external information. The purpose of this article is to evaluate, empirically, characteristics of a representative set of internal clustering validation indices with many datasets. The prototype-based clustering framework includes multiple, classical and robust, statistical estimates of cluster location so that the overall setting of the paper is novel. General observations on the quality of validation indices and on the behavior of different variants of clustering algorithms will be given.
dc.language.isoeng
dc.publisherMDPI
dc.relation.ispartofseriesAlgorithms
dc.subject.otherprototype-based clustering
dc.subject.otherclustering validation index
dc.subject.otherrobust statistics
dc.titleComparison of Internal Clustering Validation Indices for Prototype-Based Clustering
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201711204306
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2017-11-20T13:15:05Z
dc.type.coarjournal article
dc.description.reviewstatuspeerReviewed
dc.relation.issn1999-4893
dc.relation.numberinseries3
dc.relation.volume10
dc.type.versionpublishedVersion
dc.rights.copyright© 2017 by the Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
dc.rights.accesslevelopenAccessfi
dc.subject.ysotiedonlouhinta
dc.subject.ysoalgoritmit
jyx.subject.urihttp://www.yso.fi/onto/yso/p5520
jyx.subject.urihttp://www.yso.fi/onto/yso/p14524
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.3390/a10030105


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© 2017 by the Authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license.
Except where otherwise noted, this item's license is described as © 2017 by the Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.