Abstract
AbstractBy viewing the training of classifiers as an optimisation problem, we have developed a method in this paper to train a new type of nearest centroid classifier with multiple centroids per class, using Particle Swarm Optimisation (PSO). The developed method has been compared to an earlier PSO classification algorithm, and was found to have partial success. Additionally, both the developed algorithm, and the earlier PSO algorithm have been implemented on the GPU, with results showing at least one order of magnitude difference between speeds of the GPU and sequential CPU implementations on most data sets.KeywordsParticle Swarm OptimisationParticle SwarmShared MemoryParticle Swarm Optimisation AlgorithmGlobal MemoryThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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