Title Of Paper:
 
 
SPATIAL BIAS CORRECTION BASED ON GAUSSIAN KERNEL FUZZY C MEANS IN CLUSTERING
Author's Name :  D.Vanisri
KeyWords:  Clustering, Fuzzy C-Means, BCFCM, KFCM and GKFCM.
Pages:  1 -8
Volume: 2
Issue: 12
Year: 2014
Abstract:
 

Clustering is the process of grouping data objects into set of disjointed classes called clusters so that objects within a class are highly similar to one another and dissimilar to the objects in other classes. K-means (KM) and Fuzzy c-means (FCM) algorithms are popular and powerful methods for cluster analysis. However, the KM and FCM algorithms have considerable trouble in a noisy environment and are inaccurate with large numbers of different sample sized clusters. The Kernel based Fuzzy C-Means (KFCM) clustering is moreover studied with associated cluster validity measures. Many numerical simulations are used to evaluate whether or not the kernelized measures are adequate for ordinary ball-shaped clusters. Finally, a new class of kernel functions is Gaussian kernel based Fuzzy C-Means (GKFCM) is proposed in this research. The proposed GKFCM algorithm becomes a generalized type of, BCFCM, and KFCM algorithms and presents with more efficiency and robustness.

Full Text: