Semi-supervised Affinity Propagation clustering

embed Silhouette index into iterations of Affinity propagation clustering to supervise its running
2.2K Downloads
Updated 1 Jul 2009

View License

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 (https://www.mathworks.com/matlabcentral/fileexchange/18245-semi-supervised-affinity-propagation-clustering), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2006a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Statistics and Machine Learning Toolbox in Help Center and MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
1.1.0.0

update the license

1.0.0.0

help file is updated