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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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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

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Metadatos del ítem

Título: Geometrical codification for clustering mixed categorical and numerical databases
Autor: Barceló Rico, Fátima Diez, José-Luís
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica
Fecha difusión:
Resumen:
[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 ...[+]
Palabras clave: Clustering , Codification error , Data conversion , k-means , Mixed data , Categorical attributes , General method , Input matrices , k-Means algorithm , Mixed database , Spherical coordinates , Benchmarking , Database systems , Clustering algorithms
Derechos de uso: Reserva de todos los derechos
Fuente:
Journal of Intelligent Information Systems. (issn: 0925-9902 )
DOI: 10.1007/s10844-011-0187-y
Editorial:
SPRINGER
Versión del editor: http://doi.org/10.1007/s10844-011-0187-y
Código del Proyecto:
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/
Agradecimientos:
The authors acknowledge the partial funding of this work by the National projects DPI2007-66728-C02-01 and DPI2008-06737-C02-01.
Tipo: Artículo

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