Code covered by the BSD License
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[idx,netsim,dpsim,expref,pref...
Finds approximately k clusters using affinity propagation (BJ Frey and
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[idx,netsim,dpsim,expref,pref...
[idx,netsim,dpsim,expref,pref]=apclusterK(s,k)
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[idx,netsim,i,unconverged,dps...
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data_load(sw,alabel,nrow,sima...
taking true class labels from a data file
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ind2cluster(labels)
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simatrix_ap(data,type,chois)
data: a matrix with each column representing a variable.
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similarity_euclid(data,vararg...
input: data --- observations x dimensions
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similarity_pearson(data,varar...
pearson coefficients between columns
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valid_errorate(labels, truela...
computing error rates for every clusters if true labels are given
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valid_external(index1,c2)
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mainFastAP_exactK.m
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View all files
Fast Affinity Propagation Clustering under Given Number of Clusters
by Kaijun Wang
03 Nov 2009
(Updated 21 Aug 2010)
Fast searching the given number of clusters
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| File Information |
| Description |
The searching process is necessary for the Affinity propagation clustering (AP) when one demands a clustering solution under given number of clusters.
The Fast AP uses multi-grid searching to reduce the calling times of AP, and improves the upper bound of preference parameter to reduce the searching scope, so that it can (largely) enhance the speed performance of AP under given number of clusters. |
| MATLAB release |
MATLAB 7.2 (R2006a)
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| Updates |
| 21 Aug 2010 |
released new version |
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