Affinity Propagation Algorithm And Its Application In The Division Of The Economic Region In China

Clustering data by identifying a subset of representative examples is important for processing densory signals and detecting patterns in data.Such "exemplars" can be found by randomly choosing an initial subset of data points and then iteratively refining it,but this works well only if that initial choice is close to a good solution.Frey and Duck devised a method called "affinity propagation," which takes ad input measures of similarity between pairs of data points. Real-valued messages are exchanged between data points until a high-quality set of ecemplars and corresponding clusters gradually emerges.In this paper,we use affinity propagation to deal with a current hot issue-the division of the economic region in China.