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IEICE Transactions on Information and Systems 2005 E88-D(12):2880-2882; doi:10.1093/ietisy/e88-d.12.2880
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Copyright © 2005 The Institute of Electronics, Information and Communication Engineers

Regular Section -- Letters -- Data Mining

Adaptive Clustering Technique Using Genetic Algorithms

Nam Hyun PARK1, Chang Wook AHN2 and Rudrapatna S. RAMAKRISHNA3

1 The author is with Tmax Soft Co., Ltd., Rep. of Korea. E-mail: nhpark{at}tmax.co.kr, 2 The author is with Samsung Advanced Institute of Technology (SAIT), Rep. of Korea., 3 The author is with Gwangju Institute of Science and Technology (GIST), Rep. of Korea.

This paper proposes a genetically inspired adaptive clustering algorithm for numerical and categorical data sets. To this end, unique encoding method and fitness functions are developed. The algorithm automatically discovers the actual number of clusters and efficiently performs clustering without unduly compromising cluster-purity. Moreover, it outperforms existing clustering algorithms.

Key Words: adaptive clustering, genetic algorithms, non-binary encoding

Manuscript received January 12, 2005. Manuscript revised June 13, 2005.


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