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The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable classification accuracy. In this paper, we propose a combination of genetic algorithms (GAs) and particle swarm optimization (PSO)(More)
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