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http://dx.doi.org/10.5391/IJFIS.2004.4.3.337

Nearest neighbor and validity-based clustering  

Son, Seo H. (Top Engineering Co., Ltd.)
Seo, Suk T. (Department of Electrical Engineering, Yeungnam University)
Kwon, Soon H. (Department of Electrical Engineering, Yeungnam University)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.4, no.3, 2004 , pp. 337-340 More about this Journal
Abstract
The clustering problem can be formulated as the problem to find the number of clusters and a partition matrix from a given data set using the iterative or non-iterative algorithms. The author proposes a nearest neighbor and validity-based clustering algorithm where each data point in the data set is linked with the nearest neighbor data point to form initial clusters and then a cluster in the initial clusters is linked with the nearest neighbor cluster to form a new cluster. The linking between clusters is continued until no more linking is possible. An optimal set of clusters is identified by using the conventional cluster validity index. Experimental results on well-known data sets are provided to show the effectiveness of the proposed clustering algorithm.
Keywords
Clustering; Nearest neighbor; Cluster validity;
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