DocumentCode
1661494
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
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1460
Lastpage
1465
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/FUZZ.2002.1006721
Filename
1006721
Link To Document