Title :
A novel cluster validity criterion for fuzzy c-regression model clustering algorithm
Author :
Kung, Chung-Chun ; Hung, Jui-Chun
Author_Institution :
Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan
Abstract :
This paper proposes a novel cluster validity criterion for the fuzzy c-regression model (FCRM) clustering algorithm. The goal of the proposed cluster validity criterion is to decide the appropriate number of clusters in a FCRM. The simulation results demonstrate its validness and effectiveness.
Keywords :
fuzzy set theory; least squares approximations; pattern clustering; statistical analysis; FCRM; effectiveness; fuzzy c-regression model clustering algorithm; novel cluster validity criterion; simulation results; validness; Algorithm design and analysis; Clustering algorithms; Data mining; Electronic mail; Entropy; Fuzzy systems; Image recognition; Partitioning algorithms;
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
DOI :
10.1109/FUZZ.2003.1206630
