Particle swarm optimization in exploratory data analysis
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
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Training neural networks is a complex task of great importance in problems of supervised learning. In this work we analyze the use of the Particle Swarm Optimization algorithm and the cooperative variant with the weight decay mechanism for neural network training aiming better generalization performances. For evaluating these algorithms we apply them to benchmark classification problems of the medical field. The results showed that the weight decay mechanism implemented improved the mean generalization control of the two algorithms in all the tested problems.