Identifying core sets of discriminatory features using particle swarm optimization

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Summary

An original two-phase feature selection method that uses particle swarm optimization (PSO), a biologically inspired optimization technique, which forms an initial core set of discriminatory features from the original feature space, which is then successively expanded by searching for additional discriminatory features.

Type
article
Published
2009-04-01
Cited by
56
References
36

Keywords

Feature selection, Particle swarm optimization, Computer science, Artificial intelligence, Pattern recognition (psychology)

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