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Clustering Algorithms Based on Mahalanobis Distances

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2 Author(s)
Jeng-Ming Yih ; Dept. of Math. Educ., Nat. Taichung Univ., Taichung, Taiwan ; Yuan-Horng Lin

Fuzzy c-means algorithm (FCM) based on Euclidean distance function converges to a local minimum of the objective function, which can only be used to detect spherical structural clusters. In this paper, an improved Fuzzy C-Means algorithm based on a Normalized Mahalanobis distance by taking a new threshold value and a new convergent process is proposed. The experimental results of three real data sets containing image classification show that our proposed new algorithm has the better performance.

Published in:

Electronic Commerce and Security (ISECS), 2010 Third International Symposium on

Date of Conference:

29-31 July 2010