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An algorithm for generating artificial test clusters

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  • Glenn Milligan

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Suggested Citation

  • Glenn Milligan, 1985. "An algorithm for generating artificial test clusters," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 123-127, March.
  • Handle: RePEc:spr:psycho:v:50:y:1985:i:1:p:123-127
    DOI: 10.1007/BF02294153
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    References listed on IDEAS

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    1. Glenn Milligan, 1981. "A monte carlo study of thirty internal criterion measures for cluster analysis," Psychometrika, Springer;The Psychometric Society, vol. 46(2), pages 187-199, June.
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    Cited by:

    1. Douglas L. Steinley, 2019. "Editorial: Journal of Classification Vol. 36-3," Journal of Classification, Springer;The Classification Society, vol. 36(3), pages 393-396, October.
    2. 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.
    3. Mingoti, Sueli A. & Lima, Joab O., 2006. "Comparing SOM neural network with Fuzzy c-means, K-means and traditional hierarchical clustering algorithms," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1742-1759, November.
    4. Balakrishnan, P. V. (Sundar) & Cooper, Martha C. & Jacob, Varghese S. & Lewis, Phillip A., 1996. "Comparative performance of the FSCL neural net and K-means algorithm for market segmentation," European Journal of Operational Research, Elsevier, vol. 93(2), pages 346-357, September.
    5. Jerzy Korzeniewski, 2013. "Empirical Evaluation of OCLUS and GenRandomClust Algorithms of Generating Cluster Structures," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(3), pages 487-494, September.
    6. Mangiameli, Paul & Chen, Shaw K. & West, David, 1996. "A comparison of SOM neural network and hierarchical clustering methods," European Journal of Operational Research, Elsevier, vol. 93(2), pages 402-417, September.
    7. Glenn Milligan & Martha Cooper, 1988. "A study of standardization of variables in cluster analysis," Journal of Classification, Springer;The Classification Society, vol. 5(2), pages 181-204, September.
    8. Joeri Hofmans & Eva Ceulemans & Douglas Steinley & Iven Mechelen, 2015. "On the Added Value of Bootstrap Analysis for K-Means Clustering," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 268-284, July.
    9. Niels Waller & Heather Kaiser & Janine Illian & Mike Manry, 1998. "A comparison of the classification capabilities of the 1-dimensional kohonen neural network with two pratitioning and three hierarchical cluster analysis algorithms," Psychometrika, Springer;The Psychometric Society, vol. 63(1), pages 5-22, March.
    10. 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.
    11. 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.
    12. Douglas Steinley, 2007. "Validating Clusters with the Lower Bound for Sum-of-Squares Error," Psychometrika, Springer;The Psychometric Society, vol. 72(1), pages 93-106, March.
    13. Chen, S. K. & Mangiameli, P. & West, D., 1995. "The comparative ability of self-organizing neural networks to define cluster structure," Omega, Elsevier, vol. 23(3), pages 271-279, June.
    14. J. Fernando Vera & Rodrigo Macías, 2017. "Variance-Based Cluster Selection Criteria in a K-Means Framework for One-Mode Dissimilarity Data," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 275-294, June.
    15. Michael Brusco & Douglas Steinley, 2007. "A Comparison of Heuristic Procedures for Minimum Within-Cluster Sums of Squares Partitioning," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 583-600, December.
    16. Roberto Rocci & Maurizio Vichi, 2005. "Three-Mode Component Analysis with Crisp or Fuzzy Partition of Units," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 715-736, December.

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