DocumentCode :
1563941
Title :
A new weighting fuzzy c-means algorithm
Author :
Yu, Jian ; Houkuan Huang
Author_Institution :
Dept. of Comput. Sci. & Technol., Northern Jiao Tong Univ., Beijing, China
Volume :
2
fYear :
2003
Firstpage :
896
Abstract :
It is always supposed that each cluster has almost equal number of points when carrying out the FCM. However, this assumption may not hold in practice. In this paper, we propose a novel fuzzy c-means algorithm based on the definition of generalized mean, weighting fuzzy c-means algorithms (WFCM). Noticing that the Gath-Geva fuzzy clustering algorithm considers the size of the clusters, we compare the performance between the WFCM and the Gath-Geva fuzzy clustering algorithms by numerical experiments. Moreover, we offer a theoretical threshold to choose an appropriate weighting exponent in the WFCM, which is also valid for the FCM, the numeric experiments verify such conclusion.
Keywords :
fuzzy logic; fuzzy set theory; generalisation (artificial intelligence); pattern clustering; Gath-Geva fuzzy clustering algorithm; numerical experiments; performance evaluation; weighting exponent; weighting fuzzy c means algorithm; Algorithm design and analysis; Clustering algorithms; Computer science; Equations; Image analysis; Image databases; Image processing; Image recognition; Process design; Spatial databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
Type :
conf
DOI :
10.1109/FUZZ.2003.1206550
Filename :
1206550
Link To Document :
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