Generalized fuzzy clustering method

• Autorzy: Przybyła T. , Roj D. , Jeżewski J. , Matonia A.
• Języki publikacji: EN

Abstrakty

EN

This paper presents a new hybrid fuzzy clustering method. In the proposed method, cluster prototypes are values that minimize the introduced generalized cost function. The proposed method can be considered as a generalization of fuzzy c–means (FCM) method as well as the fuzzy c–median (FCMed) clustering method. The generalization of the cluster cost function is made by applying the Lp norm. The values that minimize the proposed cost function have been chosen as the group prototypes. The weighted myriad is the special case of the group prototype, when the Lp norm is the L2 (Euclidean) norm. The cluster prototypes are the weighted meridians for the L1 norm. Artificial data set is used to demonstrate the performance of proposed method.

Słowa kluczowe

EN

fuzzy clustering; fuzzy meridian; fuzzy myriad; generalized cost function; unsupervised clustering

PL

grupowanie rozmyte; uogólniona funkcja kosztów; grupowanie nienadzorowane

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2010
• Tom: Vol. 16
• Strony: 69--76
• Opis fizyczny: Bibliogr. 16 poz., rys., tab.

Twórcy

autor

Przybyła T.

• Silesian University of Technology, Institute of Electronics, Akademicka 16, 44-100 Gliwice, Poland

autor

Roj D.

autor

Jeżewski J.

autor

Matonia A.

Bibliografia

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