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Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures

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  • Douglas Steinley

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  • Michael Brusco

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  • Douglas Steinley & Michael Brusco, 2008. "Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures," Psychometrika, Springer;The Psychometric Society, vol. 73(1), pages 125-144, March.
  • Handle: RePEc:spr:psycho:v:73:y:2008:i:1:p:125-144 DOI: 10.1007/s11336-007-9019-y
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    References listed on IDEAS

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    1. Paul Green & Jonathan Kim & Frank Carmone, 1990. "A preliminary study of optimal variable weighting in k-means clustering," Journal of Classification, Springer;The Classification Society, vol. 7(2), pages 271-285, September.
    2. Lawrence Hubert & Phipps Arabie, 1985. "Comparing partitions," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 193-218, December.
    3. Montanari, Angela & Lizzani, Laura, 2001. "A projection pursuit approach to variable selection," Computational Statistics & Data Analysis, Elsevier, pages 463-473.
    4. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
    5. Glenn Milligan, 1980. "An examination of the effect of six types of error perturbation on fifteen clustering algorithms," Psychometrika, Springer;The Psychometric Society, pages 325-342.
    6. Glenn Milligan, 1985. "An algorithm for generating artificial test clusters," Psychometrika, Springer;The Psychometric Society, pages 123-127.
    7. Douglas Steinley & Robert Henson, 2005. "OCLUS: An Analytic Method for Generating Clusters with Known Overlap," Journal of Classification, Springer;The Classification Society, vol. 22(2), pages 221-250, September.
    8. Michael Brusco & J. Cradit, 2001. "A variable-selection heuristic for K-means clustering," Psychometrika, Springer;The Psychometric Society, vol. 66(2), pages 249-270, June.
    9. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    10. E. Fowlkes & R. Gnanadesikan & J. Kettenring, 1988. "Variable selection in clustering," Journal of Classification, Springer;The Classification Society, vol. 5(2), pages 205-228, September.
    11. Raftery, Adrian E. & Dean, Nema, 2006. "Variable Selection for Model-Based Clustering," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 168-178, March.
    12. Glenn Milligan, 1989. "A validation study of a variable weighting algorithm for cluster analysis," Journal of Classification, Springer;The Classification Society, vol. 6(1), pages 53-71, December.
    13. Wayne DeSarbo & J. Carroll & Linda Clark & Paul Green, 1984. "Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables," Psychometrika, Springer;The Psychometric Society, vol. 49(1), pages 57-78, March.
    14. R. Gnanadesikan & J. Kettenring & S. Tsao, 1995. "Weighting and selection of variables for cluster analysis," Journal of Classification, Springer;The Classification Society, vol. 12(1), pages 113-136, March.
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    Cited by:

    1. repec:spr:jclass:v:34:y:2017:i:3:d:10.1007_s00357-017-9240-z is not listed on IDEAS
    2. Timmerman, Marieke E. & Ceulemans, Eva & Kiers, Henk A.L. & Vichi, Maurizio, 2010. "Factorial and reduced K-means reconsidered," Computational Statistics & Data Analysis, Elsevier, pages 1858-1871.
    3. Andrews, Rick L. & Brusco, Michael J. & Currim, Imran S., 2010. "Amalgamation of partitions from multiple segmentation bases: A comparison of non-model-based and model-based methods," European Journal of Operational Research, Elsevier, vol. 201(2), pages 608-618, March.
    4. Brusco, Michael J. & Steinley, Douglas, 2011. "Exact and approximate algorithms for variable selection in linear discriminant analysis," Computational Statistics & Data Analysis, Elsevier, pages 123-131.
    5. Jerzy Korzeniewski, 2016. "New Method Of Variable Selection For Binary Data Cluster Analysis," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 17(2), pages 295-304, June.
    6. Michael Brusco & Hans-Friedrich Köhn & Douglas Steinley, 2015. "An Exact Method for Partitioning Dichotomous Items Within the Framework of the Monotone Homogeneity Model," Psychometrika, Springer;The Psychometric Society, pages 949-967.
    7. repec:exl:29stat:v:17:y:2016:i:2:p:295-304 is not listed on IDEAS
    8. Michael Brusco & Renu Singh & Douglas Steinley, 2009. "Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis," Psychometrika, Springer;The Psychometric Society, pages 705-726.
    9. Isabella Morlini & Sergio Zani, 2012. "Dissimilarity and similarity measures for comparing dendrograms and their applications," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(2), pages 85-105, July.
    10. Hsu, David, 2015. "Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data," Applied Energy, Elsevier, pages 153-163.
    11. Gao, Jinxin & Hitchcock, David B., 2010. "James-Stein shrinkage to improve k-means cluster analysis," Computational Statistics & Data Analysis, Elsevier, pages 2113-2127.
    12. Léna CAREL & Pierre ALQUIER, 2017. "Simultaneous Dimension Reduction and Clustering via the NMF-EM Algorithm," Working Papers 2017-38, Center for Research in Economics and Statistics.
    13. Pacheco, Joaquín & Casado, Silvia & Porras, Santiago, 2013. "Exact methods for variable selection in principal component analysis: Guide functions and pre-selection," Computational Statistics & Data Analysis, Elsevier, pages 95-111.

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    Keywords

    cluster analysis; variable selection;

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