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Author Runkler, T.A.
Sponsorship IEEE ♦ IEEE Neural Networks Soc
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2005
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Fuzzy sets ♦ Communications technology ♦ Shape ♦ Scattering ♦ Clustering algorithms ♦ Fuzzy systems ♦ Iterative algorithms ♦ Computational complexity
Abstract This paper deals with clustering relational data that can be (at least approximately) represented by object data with ellipsoidal clusters. Conventional relational clustering models such as relational fuzzy c-means or relational fuzzy c-medoids produce bad results for this family of relational data, because they do not consider the cluster shape. In this paper, we develop a Gustafson Kessel model where the cluster centers are medoids. For relational data, the scatter matrices and the matrix distances are locally computed using triangulation. The resulting RGKMdd algorithm produces very good results for the family of relational data specified above
Description Author affiliation: Dept. of Neural Comput., Siemens AG, Munich (Runkler, T.A.)
ISBN 0780391594
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-05-25
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 1.90 MB
Page Count 6
Starting Page 73
Ending Page 78


Source: IEEE Xplore Digital Library