Title :
Fuzzy c-regression model with a new cluster validity criterion
Author :
Kung, Chung-Chun ; Lin, Chih-Chien
Author_Institution :
Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan
fDate :
6/24/1905 12:00:00 AM
Abstract :
In this paper, a new cluster validity criterion designed for a fuzzy c-regression model algorithm with hyperplane-shaped cluster representatives is proposed. The simulation results show that the proposed cluster validity criterion is able to indicate the number of clusters correctly if the data have a hyperplane-type structure
Keywords :
data analysis; data structures; fuzzy set theory; modelling; pattern clustering; statistical analysis; cluster number; cluster validity criterion; fuzzy c-means algorithm; fuzzy c-regression model; hyperplane-shaped cluster representatives; hyperplane-type data structure; simulation; Algorithm design and analysis; Clustering algorithms; Entropy; Fuzzy sets; Parameter estimation; Partitioning algorithms; Yield estimation;
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.2002.1006728
