Context Evaluation for Fuzzy Conditional Clustering

• Autorzy: Czabański R.
• Języki publikacji: EN

Abstrakty

EN

In this paper an algorithm of fuzzy context evaluation for generalized conditional weighted fuzzy clustering is desribed. To find the unknown context values a preliminary clustering algorithm is employed. The application of several clustering methods in the process of context estimation is presented. An example of the Iris data classification problem is shown to illustrate the advantages of the proposed algorithm.

Słowa kluczowe

EN

fuzzy clustering; clustering methods; fuzzy context

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2002
• Tom: Vol. 50, Nr 1
• Strony: 71--79
• Opis fizyczny: Bibliogr. 7 poz., 3 rys., 1 tab.

Twórcy

autor

Czabański R.

• Institute of Electronics Silesian University of Technology, Akademicka 16, 44-101 Gliwice, Poland (Instytut Elektroniki Politechniki Śląskiej)

Bibliografia

• [1] J. C. Bezdek, Pattern recognition with fuzzy objective function algorithms, Plenum, New York 1981.
• [2] E. Czogata, J. Leski, Fuzzy and neuro-fuzzy intelligent systems, Springer-Verlag 2000.
• [3] N.B. Karayiannis, Generalized fuzzy c-Means algorithms, Proc. of the Fifth IEEE Int. Conf. on Fuzzy Systems, IEEE Press, (1996) 1036-1042.
• [4] P.R. Kersten, Fuzzy order statistics and their application to fuzzy clustering, IEEE Trans. on Fuzzy Systems, 7 (1999) 708-712.
• [5] R. Krishnapuram, J.M. Keller, A possibilistic approach to clustering, IEEE Trans. on Fuzzy Systems, 1 (1993) 98-110.
• [6] N.R. Pal, K. Pal, J.C. Bezdek, A mized c-means clustering model, Proc. of the Sixth IEEE Int. Conf. on Fuzzy Systems, IEEE Press, (1997) 11-21.
• [7] W. Pedrycz, Conditional fuzzy clustering in the design of radial basis function neural networks, IEEE Trans. on Neural Networks, 9 (1998) 601-612.