Semi-supervised Affinity Propagation clustering

embed Silhouette index into iterations of Affinity propagation clustering to supervise its running
Updated 1 Jul 2009

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Affinity propagation clustering (AP) is a clustering algorithm proposed in "Brendan J. Frey and Delbert

Dueck. Clustering by Passing Messages Between Data Points. Science 315, 972 (2007)". It has some advantages: speed, general applicability, and suitable for large number of clusters.

Semi-supervised AP improves AP by: embedding Silhouette indices into the programs of AP to supervise the running of AP, so that the AP will give its optimal clustering solution.

The programs of semi-supervised AP are suitable for the person who has interests in studying or improving AP algorithm, and then the semi-supervised AP may be an example for reference.

Cite As

Kaijun Wang (2024). Semi-supervised Affinity Propagation clustering (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2006a
Compatible with any release
Platform Compatibility
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