ClusterTools Contents

ClusterTools User Guide



Examplar clustering, wrapper around EXEMPLAR


 D Square dissimilarity matrix, size M*M, dataset or doubles
 K Scalar or a vector of length N with desired numbers of clusters.  Default is a set of N clusterings with numbers that naturally  arise from the data.
 NEST Logical, if TRUE a nested result is returned in case of  multi-level clustering. Default is TRUE unless K is given, as  nesting conflicts with demanding a number of clusters.

 LAB M*N array with the results of the multi-level clusterings for the
 M objects. The columns refer to the N clusterings. They yield for  the objects the prototype indices of the clusters they belong to.


This routine performs a clustering based on message passing between data  points, see [1]. It is a wrapper around EXEMPLAR and uses its default  parameter settings. EXEMPLAR does not return a predefined number of  clusters. Therefore, if K is defined clustering is redefined by RECLUSTK,  possibly at the cost of performance.


[1] B.J. Frey and D. Dueck, Clustering by passing messages between data points, Science, vol. 315, pp. 972-976, 2007

See also

datasets, mappings, exemplar, dclustm, dclusth, dclustk, clusteval, clustcerr, clustc, reclustk,

ClusterTools Contents

ClusterTools User Guide

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