dcluste
DCLUSTE
Examplar clustering, wrapper around EXEMPLAR
LAB = DCLUSTE(D,K)
LAB = D*DCLUSTE(K)
Input  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 multilevel clustering. Default is TRUE unless K is given, as nesting conflicts with demanding a number of clusters. 
Output  LAB  M*N array with the results of the multilevel 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. 
Description 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. Reference(s)[1] B.J. Frey and D. Dueck, Clustering by passing messages between data points, Science, vol. 315, pp. 972976, 2007 See also
datasets, mappings, exemplar, dclustm, dclusth, dclustk, clusteval, clustcerr, clustc, reclustk, This file has been automatically generated. If badly readable, use the helpcommand in Matlab. 
