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Identifying genuine clusters in a classification

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  • Gordon, A. D.

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  • Gordon, A. D., 1994. "Identifying genuine clusters in a classification," Computational Statistics & Data Analysis, Elsevier, vol. 18(5), pages 561-581, December.
    • Handle: RePEc:eee:csdana:v:18:y:1994:i:5:p:561-581
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    Cited by:

    1. 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.
    2. 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.
    3. Michael Greenacre, 2011. "A Simple Permutation Test for Clusteredness," Working Papers 555, Barcelona School of Economics.
    4. Remizov, Alexey & Memon, Shazim Ali & Kim, Jong R., 2024. "Novel building energy performance-based climate zoning enhanced with spatial constraint," Applied Energy, Elsevier, vol. 355(C).
    5. Z. Volkovich & D. Toledano-Kitai & G.-W. Weber, 2013. "Self-learning K-means clustering: a global optimization approach," Journal of Global Optimization, Springer, vol. 56(2), pages 219-232, June.

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