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MS-BACO: A new Model Selection algorithm using Binary Ant Colony Optimization for neural complexity and error reduction
Stabilizing the complexity of Feedforward Neural Networks (FNNs) for the given approximation task can be managed by defining an appropriate model magnitude which is also greatly correlated with the generalization quality and computational efficiency.
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