A SELECTIVE CONSTRUCTING APPROACH TO NEURAL NETWORK ENSEMBLE
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Abstract
To improve the ability of generalization, a selective constructing approach to neural network ensemble is proposed, in which the genetic algorithm is used to select part of the trained individual networks to be ensembled. Theoretical analyses and experimental results show that this approach outperforms the traditional ones that ensemble all of the individual networks.
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