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A global Approach to the Comparison of Clustering Results

dc.contributor.authorSilva, Osvaldo
dc.contributor.authorBacelar-Nicolau, Helena
dc.contributor.authorNicolau, Fernando C.
dc.date.accessioned2014-02-05T15:53:47Z
dc.date.available2014-02-05T15:53:47Z
dc.date.issued2012
dc.date.updated2014-01-29T12:42:09Z
dc.descriptionCopyright © 2012 Walter de Gruyter GmbH.en
dc.description.abstractThe discovery of knowledge in the case of Hierarchical Cluster Analysis (HCA) depends on many factors, such as the clustering algorithms applied and the strategies developed in the initialstage of Cluster Analysis. We present a global approach for evaluating the quality of clustering results and making a comparison among different clustering algorithms using the relevant information available (e.g. the stability, isolation and homogeneity of the clusters). In addition, we present a visual method to facilitate evaluation of the quality of the partitions, allowing identification of the similarities and differences between partitions, as well as the behaviour of the elements in the partitions. We illustrate our approach using a complex and heterogeneous dataset (real horse data) taken from the literature. We apply HCA based on the generalized affinity coefficient (similarity coefficient) to the case of complex data (symbolic data), combined with 26 (classic and probabilistic) clustering algorithms. Finally, we discuss the obtained results and the contribution of this approach to gaining better knowledge of the structure of data.en
dc.identifier.citationSilva, Osvaldo; Bacelar-Nicolau, Helena; Nicolau, Fernando, C. (2012). "A global Approach to the Comparison of Clustering Results", Biometrical Letters, 49(2), 135-147. ISSN (Print) 1896-3811, DOI: 10.2478/bile-2013-0010.en
dc.identifier.issn1896-3811 (Print)
dc.identifier.urihttp://hdl.handle.net/10400.3/2706
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherWalter de Gruyteren
dc.relation.publisherversionhttp://www.degruyter.com/view/j/bile.2012.49.issue-2/bile-2013-0010/bile-2013-0010.xmlpor
dc.subjectCluster Analysisen
dc.subjectVL Methodologyen
dc.subjectAffinity Coefficienten
dc.subjectComparing Partitionsen
dc.subjectCluster Stabilityen
dc.subjectCluster Validationen
dc.titleA global Approach to the Comparison of Clustering Resultsen
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlacePoznań, Polandpor
oaire.citation.endPage147por
oaire.citation.issue(2)por
oaire.citation.startPage135por
oaire.citation.titleBiometrical Lettersen
oaire.citation.volume49por
rcaap.rightsopenAccesspor
rcaap.typearticlepor

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