Heuristic configuration of single hidden-layer feed-forward neural networks


For optimum statistical classification and generalization with single hidden-layer neural network models, two tasks must be performed: (a) learning the best set of weights for a network of k hidden units and (b) determining k, the best complexity fit. We contrast two approaches to construction of neural network classifiers: (a) standard back-propagation as… (More)
DOI: 10.1007/BF00058649


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