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A Study on K -Means Clustering

  • Bae, Wha-Soo (Department of Data Science, Inje University) ;
  • Roh, Se-Won (Department of Data Science, Inje University)
  • 발행 : 2005.08.01

초록

This paper aims at studying on K-means Clustering focusing on initialization which affect the clustering results in K-means cluster analysis. The four different methods(the MA method, the KA method, the Max-Min method and the Space Partition method) were compared and the clustering result shows that there were some differences among these methods, especially that the MA method sometimes leads to incorrect clustering due to the inappropriate initialization depending on the types of data and the Max-Min method is shown to be more effective than other methods especially when the data size is large.

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참고문헌

  1. Anderberg M.R (1973). Cluster Analysis for Applications. Academic Press, New York
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  4. Kaufman L and Rousseeuw P.J(990). Finding Groups in Data. An Introduction to Cluster Analysis. John Wiley & Sons, Canada
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