Skip navigation
Por favor, use este identificador para citar o enlazar este ítem: http://uvadoc.uva.es/handle/10324/5963
Título: Robust constrained fuzzy clustering
Autor: García Escudero, Luis Ángel
Fritz, Heinrich
Mayo Iscar, Agustín
Editor: Universidad de Valladolid. Facultad de Ciencias
Año del Documento: 2013
Documento Fuente: Fritz, H.; García-Escudero, L.A. and Mayo-Iscar; A. (2013) “Robust constrained fuzzy clustering” Information Sciences, Vol. 245, Pag. 38-52.
Resumen: It is well-known that outliers and noisy data can be very harmful when applying clustering methods. Several fuzzy clustering methods which are able to handle the presence of noise have been proposed. In this work, we propose a robust clustering approach called F-TCLUST based on an “impartial” (i.e., self-determined by data) trimming. The proposed approach considers an eigenvalue ratio constraint that makes it a mathematically well-defined problem and serves to control the allowed differences among cluster scatters. A computationally feasible algorithm is proposed for its practical implementation. Some guidelines about how to choose the parameters controlling the performance of the fuzzy clustering procedure are also given.
Materias (normalizadas): Statistics
Departamento: Estadística e IO
Idioma: eng
URI: http://uvadoc.uva.es/handle/10324/5963
Derechos: info:eu-repo/semantics/openAccess
An error occurred on the license name.
Aparece en las colecciones:DEP24 - Otros Documentos (Informes, Memorias, Documentos de Trabajo, etc)

Ficheros en este ítem:
Fichero Descripción TamañoFormato 
robust_fuzzy_clustering.pdfArticulo1,65 MBAdobe PDFThumbnail
Visualizar/Abrir


Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons Creative Commons

Comentarios
Universidad de Valladolid
Powered by MIT's. DSpace software, Version 5.5