Species Associations and Conditional Clustering: Clustering With or Without Pairwise Resemblances

  • L. P. Lefkovitch
Part of the NATO ASI Series book series (volume 14)


Traditional procedures for clustering objects consist of two steps: measuring pairwise resemblance based on the attributes, and a clustering algorithm. The use of pairwise resemblances can be avoided; a set of objects can be represented as a set of lists of attribute states; an application of the Laplace indifference principle then allows an estimate to be made of the probability of each list as representative of an association of objects. By use of set-covering procedures, the object associations having maximum joint probability are found. The procedure is generalized to multistate unordered and ordered attributes, to frequencies, and to directly obtained relational data.


Optimal Covering Species Association Initial Pair Missing Element Fortran Subroutine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1987

Authors and Affiliations

  • L. P. Lefkovitch
    • 1
  1. 1.Engineering and Statistical Research CentreAgriculture CanadaOttawaCanada

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