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A Note on Maximizing the Agreement Between Partitions: A Stepwise Optimal Algorithm and Some Properties

Listed author(s):
  • Douglas Steinley


  • Gretchen Hendrickson
  • Michael Brusco
Registered author(s):

    Building on Brusco and Steinley (2008), a computationally efficient stepwise optimal heuristic is provided for maximizing the adjusted Rand index (Hubert and Arabie 1985). The proposed algorithm is different than other methods for estimating the maximum value for the adjusted Rand index (e.g., Messatfa 1992) in that it does not rely on mathematical programming; consequently, problems of much larger size can be handled. Using the proposed method, various characteristics of the adjusted Rand index are explored and presented. Copyright Classification Society of North America 2015

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    Article provided by Springer & The Classification Society in its journal Journal of Classification.

    Volume (Year): 32 (2015)
    Issue (Month): 1 (April)
    Pages: 114-126

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    Handle: RePEc:spr:jclass:v:32:y:2015:i:1:p:114-126
    DOI: 10.1007/s00357-015-9169-z
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    References listed on IDEAS
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    1. H. Messatfa, 1992. "An algorithm to maximize the agreement between partitions," Journal of Classification, Springer;The Classification Society, vol. 9(1), pages 5-15, January.
    2. Michael Brusco & Douglas Steinley, 2008. "A Binary Integer Program to Maximize the Agreement Between Partitions," Journal of Classification, Springer;The Classification Society, vol. 25(2), pages 185-193, November.
    3. 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.
    4. Glenn Milligan & Martha Cooper, 1985. "An examination of procedures for determining the number of clusters in a data set," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 159-179, June.
    5. Douglas Steinley & Michael J. Brusco, 2007. "Initializing K-means Batch Clustering: A Critical Evaluation of Several Techniques," Journal of Classification, Springer;The Classification Society, vol. 24(1), pages 99-121, June.
    6. Ahmed N. Albatineh & Magdalena Niewiadomska-Bugaj & Daniel Mihalko, 2006. "On Similarity Indices and Correction for Chance Agreement," Journal of Classification, Springer;The Classification Society, vol. 23(2), pages 301-313, September.
    7. 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.
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