K-Mean Clustering and PSO: A Review
نویسندگان
چکیده
Clustering is a method which divides data objects into groups based on the information found in data that describes the objects and relationships among them. There are a variety of algorithms have been developed in recent years for solving problems of data clustering. Data clustering algorithms can be either hierarchical or partitioned. Most promising among them are K-means algorithm which is partitioned clustering algorithm .Moreover k-mean Algorithm is an efficient Clustering Algorithm but it can generate a local optimal solution. On the other hand, Particle Swarm Optimization is used for global optimization. Thus K-means algorithm shows improved results when used with the combination of PSO (Particle Swarm Optimization).
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