Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Application of Principal Component Analysis Prior to Cluster Analysis in the Concept of Informative Variables

  • Chae, Seong-San (Department of Information and Statistics, Daejeon University)
  • Published : 2003.12.01
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Abstract

Results of using principal component analysis prior to cluster analysis are compared with results from applying agglomerative clustering algorithm alone. The retrieval ability of the agglomerative clustering algorithm is improved by using principal components prior to cluster analysis in some situations. On the other hand, the loss in retrieval ability for the agglomerative clustering algorithms decreases, as the number of informative variables increases, where the informative variables are the variables that have distinct information(or, necessary information) compared to other variables.

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