Semi-supervised Affinity Propagation clustering: ind2cluster(labels) - File Exchange

Code covered by the BSD License

Highlights from
Semi-supervised Affinity Propagation clustering

... Handle arguments to function
[idx,netsim,dpsim,expref,unco...
ind2cluster(labels)
similarity_euclid(data,vararg...
similarity_pearson(data) pearson coefficients between every two columns
similarity_pearsonC(data, C) pearson coefficients between every column and the center
valid_errorate(labels, truela... computing error rates for every clusters if true labels are given
valid_external(index1,c2)
valid_sumpearson(data,labels,... within-, between-cluster and total sum of squares
valid_sumsqures(data,labels,k... data: a matrix with each column representing a variable.
test_APclustering.m
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from Semi-supervised Affinity Propagation clustering by Kaijun Wang
embed Silhouette index into iterations of Affinity propagation clustering to supervise its running

ind2cluster(labels)

function [clusters, newlabels] = ind2cluster(labels)

C = unique(labels);
newlabels = labels;
k = length(C);
clusters = cell(1,k);
for i = 1:k
  ind = find(labels==C(i));
  clusters{i} = ind;
  newlabels(ind) = i;
end

Highlights from Semi-supervised Affinity Propagation clustering

Highlights from
Semi-supervised Affinity Propagation clustering