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Measuring the influence of individual data points in a cluster analysis

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  • Glenn Milligan
  • Richard Cheng

Abstract

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Suggested Citation

  • Glenn Milligan & Richard Cheng, 1996. "Measuring the influence of individual data points in a cluster analysis," Journal of Classification, Springer;The Classification Society, vol. 13(2), pages 315-335, September.
    • Handle: RePEc:spr:jclass:v:13:y:1996:i:2:p:315-335
    DOI: 10.1007/BF01246105
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    References listed on IDEAS

    as
    1. Robert Sokal & Junhyong Kim & F. Rohlt, 1992. "Character and OTU stability in five taxonomic groups," Journal of Classification, Springer;The Classification Society, vol. 9(1), pages 117-140, January.
    2. Glenn Milligan, 1980. "An examination of the effect of six types of error perturbation on fifteen clustering algorithms," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 325-342, September.
    3. Glenn Milligan, 1985. "An algorithm for generating artificial test clusters," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 123-127, March.
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    Citations

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    Cited by:

    1. Z. Volkovich & Z. Barzily & G.-W. Weber & D. Toledano-Kitai & R. Avros, 2012. "An application of the minimal spanning tree approach to the cluster stability problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(1), pages 119-139, March.
    2. Salvatore Ingrassia & Antonio Punzo, 2020. "Cluster Validation for Mixtures of Regressions via the Total Sum of Squares Decomposition," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 526-547, July.
    3. Bertrand, P. & Bel Mufti, G., 2006. "Loevinger's measures of rule quality for assessing cluster stability," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 992-1015, February.
    4. Park, P.J. & Manjourides, J. & Bonetti, M. & Pagano, M., 2009. "A permutation test for determining significance of clusters with applications to spatial and gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4290-4300, October.
    5. Douglas Steinley & Gretchen Hendrickson & Michael Brusco, 2015. "A Note on Maximizing the Agreement Between Partitions: A Stepwise Optimal Algorithm and Some Properties," Journal of Classification, Springer;The Classification Society, vol. 32(1), pages 114-126, April.

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