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Please use this identifier to cite or link to this item: http://uvadoc.uva.es/handle/10324/21571
Title: Consensus-Based Agglomerative Hierarchical Clustering
Authors: García Lapresta, José Luis
Pérez Román, David
Issue Date: 2017
Publisher: Springer
Description: Producción Científica
Citation: Fuzzy Sets, Rough Sets, Multisets and Clustering. eds. V. Torra, A. Dahlbom, Y. Narukawa. Springer, 2017 (Studies in Computational Intelligence 671)
Abstract: In this contribution, we consider that a set of agents assess a set of alternatives through numbers in the unit interval. In this setting, we introduce a measure that assigns a degree of consensus to each subset of agents with respect to every subset of alternatives. This consensus measure is defined as 1 minus the outcome generated by a symmetric aggregation function to the distances between the corresponding individual assessments. We establish some properties of the consensus measure, some of them depending on the used aggregation function. We also introduce an agglomerative hierarchical clustering procedure that is generated by similarity functions based on the previous consensus measures
Keywords: Matemáticas
Operadores, Teoría de
ISBN: 978-3-319-47557-8
Sponsor: Ministerio de Economía, Industria y Competitividad (ECO2012-32178)
Junta de Castilla y León (programa de apoyo a proyectos de investigación – Ref. VA066U13)
Publisher Version: http://www.springer.com/us/book/9783319475561
Language: eng
URI: http://uvadoc.uva.es/handle/10324/21571
Rights: info:eu-repo/semantics/openAccess
Appears in Collections:DEP20 - Capítulos de monografías

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