Fuzzy C-means clustering algorithm based on kernel method

In this paper, we propose a fuzzy kernel C-means clustering algorithm (FKCM) which is based on conventional fuzzy C-means clustering algorithm (FCM). This new FKCM algorithm integrates FCM with Mercer kernel function and deals with some issues in fuzzy clustering. The properties of the new algorithms are illustrated the FKCM algorithm is not only suitable for clusters with the spherical shape, but also other non-spherical shapes such as annular ring shape effectively.

[1]  Isak Gath,et al.  Unsupervised Optimal Fuzzy Clustering , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Christopher J. C. Burges,et al.  Geometry and invariance in kernel based methods , 1999 .

[3]  Gunnar Rätsch,et al.  Input space versus feature space in kernel-based methods , 1999, IEEE Trans. Neural Networks.

[4]  Mark A. Girolami,et al.  Mercer kernel-based clustering in feature space , 2002, IEEE Trans. Neural Networks.

[5]  Z Li,et al.  KERNEL CLUSTERING ALGORITHM , 2002 .