# Clustering by Passing Messages 1.0

OS : Windows / Linux / Mac OS / BSD / Solaris

Script Licensing : Freeware

Created : Sep 17, 2007

Downloads : 1

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## Simple and effective means of clustering any data for ...

Simple and effective means of clustering any data for which a similarity matrix can be constructed. Does not require similarity matrix meet the standards for a metric. The algorithm applies in cases where the similarity matrix is not symmetric (the distance from point i to j can be different from j to i). And it does not require triangular equalities (e. g. the hypoteneus can be less than the sum of the other sides)

usage is very simple (given an m x m similarity matrix)

ex = affprop(s)

returns ex, a m x 1 vector of indices, such that ex(i) is the exemplar for the ith point.

see affyprop_demo for a complete example with simple 2d data. See reference for more complex examples including face matching.

usage is very simple (given an m x m similarity matrix)

ex = affprop(s)

returns ex, a m x 1 vector of indices, such that ex(i) is the exemplar for the ith point.

see affyprop_demo for a complete example with simple 2d data. See reference for more complex examples including face matching.

**Clustering by Passing Messages 1.0 scripting tags:**matrix, matlab, require, matlab clustering, statistics probability, passing, messages, data, clustering passing messages, point, similarity.

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