The diversity/accuracy dilemma: an empirical analysis in the context of heterogeneous ensembles
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Feature selection in heterogeneous structure of ensembles: a genetic algorithm approach
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
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The use of intelligent agents in the structure of multiclassifier systems has been investigated in order to overcome some drawbacks of these systems and, as a consequence, to improve the performance of such systems. As a result of this, the NeurAge system was proposed. This system has presented good results in some centralized and distributed classification tasks. In this paper, an investigation of using evolutionary techniques in the functioning of the NeurAge (GNeurAge) is performed. In order to do this, we are going to use genetic algorithm in two different phases: in the choice of the initial classifier; and during the functioning of NeurAge (test phase).