ASCM: An accelerated soft c-means clustering algorithm

Adel, T. and Ismail, M. (2010) ASCM: An accelerated soft c-means clustering algorithm. In: ISDA 2010 10th International Conference on Intelligent Systems Design and Applications, Cairo, Egypt, 29 Nov - 1 Dec 2010, pp. 1142-1147. ISBN 9781424481361 (doi: 10.1109/ISDA.2010.5687031)

Abstract

The advantages of soft c-means over its hard and fuzzy versions render it more attractive to use in a wide variety of applications. Its main merit lies in its relatively higher convergence speed, which is more obvious in the presence of huge high dimensional data. This work presents a new approach to accelerate the convergence of the original soft c-means. It is mainly based on an iterative optimization approach and a relaxation technique. Several low and high dimensional datasets are used to evaluate the performance of the proposed approach. Experimental results show up to 70% improvement over the original soft and fuzzy c-means algorithms.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Hesham, Dr Tameem Adel
• Authors: Adel, T., and Ismail, M.
• College/School: College of Science and Engineering > School of Computing Science
• ISSN: 2164-7143
• ISBN: 9781424481361