General bound of overfitting for MLP regression models

Multilayer perceptrons (MLP) with one hidden layer have been used for a long time to deal with non-linear regression. However, in some task, MLP's are too powerful models and a small mean square error (MSE) may be more due to overfitting than to actual modeling. If the noise of the regression m...

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Veröffentlicht in:	Neurocomputing (Amsterdam) 2012-08, Vol.90, p.106-110
1. Verfasser:	Rynkiewicz, J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Architecture Asymptotic statistic Gaussian Likelihood ratio Mathematics Mean square error Mean square values Models selection Multilayer perceptron Noise Regression Statistics Statistics Theory Tasks
Online-Zugang:	Volltext
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