Sung Suk Kim, Ho Jin Choi, Journal of Internet Computing and Services, Vol. 13, No. 5, pp. 1-8, Oct. 2012
10.7472/jksii.2012.13.5.1, Full Text:
Keywords: Sequential clustering, Mountain clustering, Local clustering, Decision rule

Abstract

In this paper, we propose a new clustering combination based on numerical data driven for rule generation mechanism. In large and complicated space, a clustering method can obtain limited performance results. To overcome the single clustering method problem, hybrid combined methods can solve problem to divided simple cluster estimation. Fundamental structure of the proposed method is combined by mountain clustering and modified Chen clustering to extract detail cluster information in complicated data distribution of non-parametric space. It has automatic rule generation ability with advanced density based operation when intelligent systems including neural networks and fuzzy inference systems can be generated by clustering results. Also, results of the mechanism will be served to information of decision support system to infer the useful knowledge. It can extend to healthcare and medical decision support system to help experts or specialists. We show and explain the usefulness of the proposed method using simulation and results.

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