[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5351/CKSS.2002.9.3.715

A Density-based Clustering Method

Ahn, Sung Mahn (School of Management Information Systems, Kookmin University)
Baik, Sung Wook (Department of Digital Contents, Sejong University)

Publication Information

Communications for Statistical Applications and Methods / v.9, no.3, 2002 , pp. 715-723 More about this Journal

Abstract

This paper is to show a clustering application of a density estimation method that utilizes the Gaussian mixture model. We define "closeness measure" as a clustering criterion to see how close given two Gaussian components are. Closeness measure is defined as the ratio of log likelihood between two Gaussian components. According to simulations using artificial data, the clustering algorithm turned out to be very powerful in that it can correctly determine clusters in complex situations, and very flexible in that it can produce different sizes of clusters based on different threshold valuesold values

Keywords

clustering method; closeness measure; Gaussian mixture model; maximum penalized likelihood; EM algorithm;

Citations & Related Records

Times Cited By KSCI : 1 (Citation Analysis)

Reference
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