Setting the Number of Clusters in K-Means Clustering

  • Myung-Hoe Huh


K-means clustering is an efficient non-hierarchical clustering method, which became widely used in data mining. In applying the method, however, one needs to specify k,the number of clusters, a priori. In this short paper, we propose an exploratory procedure for setting k using Euclidean and/or Mahalanobis inter-point distances.


Mahalanobis Distance Iris Data Multivariate Normal Distribution Exploratory Procedure Rock Crab 
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Copyright information

© The Institute of Statistical Mathematics 2002

Authors and Affiliations

  • Myung-Hoe Huh
    • 1
  1. 1.Dept. of StatisticsKorea UniversitySeoulKorea

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