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A CLUE for CLUster Ensembles

  • Kurt Hornik
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    Cluster ensembles are collections of individual solutions to a given clustering problem which are useful or necessary to consider in a wide range of applications. The R package clue provides an extensible computational environment for creating and analyzing cluster ensembles, with basic data structures for representing partitions and hierarchies, and facilities for computing on these, including methods for measuring proximity and obtaining consensus and "secondary" clusterings.

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    Article provided by American Statistical Association in its journal Journal of Statistical Software.

    Volume (Year): 14 ()
    Issue (Month): i12 ()

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    Handle: RePEc:jss:jstsof:14:i12
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    1. Leo Katz & James Powell, 1953. "A proposed index of the conformity of one sociometric measurement to another," Psychometrika, Springer, vol. 18(3), pages 249-256, September.
    2. Samuel E. Buttrey, . "Calling the lp_solve Linear Program Software from R, S-PLUS and Excel," Journal of Statistical Software, American Statistical Association, vol. 14(i04).
    3. A. Gordon & M. Vichi, 2001. "Fuzzy partition models for fitting a set of partitions," Psychometrika, Springer, vol. 66(2), pages 229-247, June.
    4. Chris Fraley & Adrian E. Raftery, 2003. "Enhanced Model-Based Clustering, Density Estimation, and Discriminant Analysis Software: MCLUST," Journal of Classification, Springer, vol. 20(2), pages 263-286, September.
    5. Anja Struyf & Mia Hubert & Peter Rousseeuw, . "Clustering in an Object-Oriented Environment," Journal of Statistical Software, American Statistical Association, vol. 1(i04).
    6. William Day, 1986. "Foreword: Comparison and consensus of classifications," Journal of Classification, Springer, vol. 3(2), pages 183-185, September.
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