Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7133
Title: New cluster validity index with fuzzy functions
Authors: Çelikyılmaz, Aslı
Türkşen, İsmail Burhan
Keywords: cluster validity
improved fuzzy clustering
Issue Date: 2007
Publisher: Springer-Verlag Berlin
Source: IFSA 2007 World Congress -- JUN 18-21, 2007 -- Cancun, MEXICO
Series/Report no.: ADVANCES IN SOFT COMPUTING
Abstract: A new cluster validity index is introduced to validate the results obtained by the recent Improved Fuzzy Clustering (IFC), which combines two different methods, i.e., fuzzy c-means clustering and fuzzy c-regression, in a novel way. Proposed validity measure determines the optimum number of clusters of the IFC based on a ratio of the compactness to separability of the clusters. The compactness is represented with: (i) the sum of the average distances of each object to their cluster centers, and (ii) the error measure of their fuzzy functions, which utilizes membership values as additional input variables. The separability is based on the ratio between: (i) the maximum distance between the cluster representatives, and (ii) the angles between their representative fuzzy functions. The experiments exhibit that the new cluster validity index is a useful function when selecting the parameters of the IFC.
URI: https://doi.org/10.1007/978-3-540-72432-2_82
https://hdl.handle.net/20.500.11851/7133
ISBN: 978-3-540-72431-5
ISSN: 1615-3871
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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