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http://dx.doi.org/10.5351/CKSS.2003.10.3.1057

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)
Publication Information
Communications for Statistical Applications and Methods / v.10, no.3, 2003 , pp. 1057-1068 More about this Journal
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.
Keywords
Agglomerative Clustering Algorithm; Principal Component Analysis; Informative Variables;
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Times Cited By KSCI : 2  (Citation Analysis)
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2 A Comparison of Agglomerative Clustering Methods with respect to Noise /
[ DuBien,J.L.;Warde,W.D. ] / Communications in Statistics, Theory and Method   DOI   ScienceOn
3 Comprehensive Identification of Cell Cycle-regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization /
[ Spellman,P.T.;Sherlock,G.;Zhang,M.Q.;Iyer,V.R.;Eisen,M.B.;Brown,P.O.;Botstein,D.;Futcher,B. ] / Molecular Biology of the Cell   DOI
4 A Mathematical Comparison of the Members of an Infinite Family of Agglomerative Clustering Algorithms /
[ DuBien,J.L.;Warde,W.D. ] / The Canadian Journal of Statistics   DOI
5 A Generalized Sorting Strategy for Computer Classification /
[ Lance,G.N.;Williams,W.T. ] / Nature
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[ Chae, Seong S.;Warde,W.D. ] / Journal of the Korean Statistical Society   과학기술학회마을
7 Results of Discriminant Analysis with Respect to Cluster Analysis Under Dimensional Reduction /
[ Chae, Seong S. ] / The Korean Communication in Sttistics   과학기술학회마을   DOI   ScienceOn
8 /
[ Johnson,R.A.;Wichern,D.W. ] / Applied Multivariate Statistical Analysis
9 Objective Criteria for the Evaluation of Clustering Methods /
[ Rand,W.M. ] / Journal of the American Statistical Association   DOI   ScienceOn
10 A General Theory of Classificatory Sorting Strategies, 1. Hierarchical Systems /
[ Lance,G.N.;Williams,W.T. ] / The Computer Journal   DOI
11 Clustering Methods for the analysis of DNA microarray data /
[ Tibshirani,R.;Hastie,T.;Eisen,M.;Ross,G.;Botstein,D.;Brown,P. ] / Technical Report, Stanford University
12 Variable Selection in Clustering /
[ Fowlkes,E.B.;Gnanadesikan,R.;Kettenring,J.P. ] / Journal of Classification   DOI
13 On using Principal Components before Separating a Mixture of Two Multivariate Normal Distributions /
[ Chang, Wei-Chien ] / Applied Statistics   DOI   ScienceOn