Hybrid fuzzy clustering using LP norms

Authors:
Tomasz Przybyła;Janusz Jeżewski;Krzysztof Horoba;Dawid Roj
Affiliations:
Silesian University of Technology, Institute of Electronics, Gliwice, Poland;Institute of Medical Technology and Equipment, Biomedical Signal Processing Department, Zabrze, Poland;Institute of Medical Technology and Equipment, Biomedical Signal Processing Department, Zabrze, Poland;Institute of Medical Technology and Equipment, Biomedical Signal Processing Department, Zabrze, Poland
Venue:
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Year:
2011

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Abstract

The fuzzy clustering methods are useful in the data mining applications. This paper describes a new fuzzy clustering method in which each cluster prototype is calculated as a value that minimizes introducted generalized cost function. The generalized cost function utilizes the Lp norm. The fuzzy meridian is a special case of cluster prototype for p = 2 as well as the fuzzy meridian for p = 1. A method for the norm selection is proposed. An example illustrating the performance of the proposed method is given.