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» Bootstrap for neural model selection
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ESANN
2003
15 years 10 days ago
Fast approximation of the bootstrap for model selection
The bootstrap resampling method may be efficiently used to estimate the generalization error of a family of nonlinear regression models, as artificial neural networks. The main dif...
Geoffroy Simon, Amaury Lendasse, Vincent Wertz, Mi...
ESANN
2000
15 years 9 days ago
Bootstrap for neural model selection
Riadh Kallel, Marie Cottrell, Vincent Vigneron
IWANN
2005
Springer
15 years 4 months ago
Input and Structure Selection for k-NN Approximator
Abstract. This paper presents k-NN as an approximator for time series prediction problems. The main advantage of this approximator is its simplicity. Despite the simplicity, k-NN c...
Antti Sorjamaa, Nima Reyhani, Amaury Lendasse
TNN
2008
93views more  TNN 2008»
14 years 10 months ago
Towards the Optimal Design of Numerical Experiments
This paper addresses the problem of the optimal design of numerical experiments for the construction of nonlinear surrogate models. We describe a new method, called learner disagre...
S. Gazut, J.-M. Martinez, Gérard Dreyfus, Y...
NN
2000
Springer
165views Neural Networks» more  NN 2000»
14 years 10 months ago
Construction of confidence intervals for neural networks based on least squares estimation
We present the theoretical results about the construction of confidence intervals for a nonlinear regression based on least squares estimation and using the linear Taylor expansio...
Isabelle Rivals, Léon Personnaz