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Geometrical codification for clustering mixed categorical and numerical databases

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Geometrical codification for clustering mixed categorical and numerical databases

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dc.contributor.author Barceló Rico, Fátima es_ES
dc.contributor.author Diez, José-Luís es_ES
dc.date.accessioned 2017-12-28T07:57:42Z
dc.date.available 2017-12-28T07:57:42Z
dc.date.issued 2012 es_ES
dc.identifier.issn 0925-9902 es_ES
dc.identifier.uri http://hdl.handle.net/10251/93511
dc.description.abstract [EN] This paper presents an alternative to cluster mixed databases. The main idea is to propose a general method to cluster mixed data sets, which is not very complex and still can reach similar levels of performance of some good algorithms. The proposed approach is based on codifying the categorical attributes and use a numerical clustering algorithm on the resulting database. The codification proposed is based on polar or spherical coordinates, it is easy to understand and to apply, the increment in the length of the input matrix is not excessively large, and the codification error can be determined for each case. The proposed codification combined with the well known k-means algorithm showed a very good performance in different benchmarks and has been compared with both, other codifications and other mixed clustering algorithms, showing a better or comparable performance in all cases. es_ES
dc.description.sponsorship The authors acknowledge the partial funding of this work by the National projects DPI2007-66728-C02-01 and DPI2008-06737-C02-01. en_EN
dc.language Inglés es_ES
dc.publisher SPRINGER es_ES
dc.relation.ispartof Journal of Intelligent Information Systems es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Clustering es_ES
dc.subject Codification error es_ES
dc.subject Data conversion es_ES
dc.subject k-means es_ES
dc.subject Mixed data es_ES
dc.subject Categorical attributes es_ES
dc.subject General method es_ES
dc.subject Input matrices es_ES
dc.subject k-Means algorithm es_ES
dc.subject Mixed database es_ES
dc.subject Spherical coordinates es_ES
dc.subject Benchmarking es_ES
dc.subject Database systems es_ES
dc.subject Clustering algorithms es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.title Geometrical codification for clustering mixed categorical and numerical databases es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10844-011-0187-y es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MEC//DPI2007-66728-C02-01/ES/CONTROL DE GLUCEMIA EN LAZO CERRADO EN PACIENTES CON DIABETES MELLITUS 1 Y PACIENTES CRITICOS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Barceló Rico, F.; Diez, J. (2012). Geometrical codification for clustering mixed categorical and numerical databases. Journal of Intelligent Information Systems. 39(1):167-185. https://doi.org/10.1007/s10844-011-0187-y es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1007/s10844-011-0187-y es_ES
dc.description.upvformatpinicio 167 es_ES
dc.description.upvformatpfin 185 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 39 es_ES
dc.description.issue 1 es_ES
dc.relation.pasarela S\208967 es_ES
dc.contributor.funder Ministerio de Educación y Ciencia es_ES
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