Title :
A modification to improve possibilistic fuzzy cluster analysis
Author :
Timm, Heiko ; Kruse, Rudolf
Author_Institution :
Dept. of Knowledge Process. & Language Eng., Otto-von-Guericke-Univ., Magdeburg, Germany
fDate :
6/24/1905 12:00:00 AM
Abstract :
We explore an approach to possibilistic fuzzy clustering that avoids a severe drawback of the conventional approach, namely that the objective function is truly minimized only if all cluster centers are identical. Our approach is based on the idea that this undesired property can be avoided if we introduce a mutual repulsion of the clusters, so that they are forced away from each other. We develop this approach for the possibilistic fuzzy c-means algorithm and the Gustafson-Kessel algorithm
Keywords :
fuzzy set theory; minimisation; pattern clustering; possibility theory; mutual repulsion; objective function minimization; possibilistic fuzzy cluster analysis; Clustering algorithms; Covariance matrix; Euclidean distance; Fuzzy sets; Humans; Knowledge engineering; Prototypes; Zinc;
Conference_Titel :
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7280-8
DOI :
10.1109/FUZZ.2002.1006721
