Semi-supervised Affinity Propagation clustering

Versione 1.1.0.0 (17,5 KB) da Kaijun Wang
embed Silhouette index into iterations of Affinity propagation clustering to supervise its running
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Aggiornato 1 lug 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.

Cita come

Kaijun Wang (2024). Semi-supervised Affinity Propagation clustering (https://www.mathworks.com/matlabcentral/fileexchange/18245-semi-supervised-affinity-propagation-clustering), MATLAB Central File Exchange. Recuperato .

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Versione Pubblicato Note della release
1.1.0.0

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1.0.0.0

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