Title :
A type-2 fuzzy C-means clustering algorithm
Author :
Rhee, Frank Chung Hoon ; Hwang, Cheul
Author_Institution :
Dept. of Electron. Eng., Hanyang Univ., Ansan, South Korea
Abstract :
This paper presents a type-2 fuzzy C-means (FCM) algorithm that is an extension of the conventional fuzzy C-means algorithm. In our proposed method, the membership values for each pattern are extended as type-2 fuzzy memberships by assigning membership grades to the type-1 memberships. In doing so, cluster centers that are estimated by type-2 memberships may converge to a more desirable location than cluster centers obtained by a type-1 FCM method in the presence of noise. Experimental results are given to show the effectiveness of our method
Keywords :
fuzzy logic; pattern clustering; FCM method; cluster centers; fuzzy C-means algorithm; membership values; pattern cluster; type-2 fuzzy C-means algorithm; Clustering algorithms; Computer vision; Equations; Fuzzy systems; Laboratories; Machine vision; Uncertainty;
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
DOI :
10.1109/NAFIPS.2001.944361
