Model Selection with Cross-Validations and Bootstraps — Application to Time Series Prediction with RBFN Models-Reference-Cited by-同舟云学术

Model Selection with Cross-Validations and Bootstraps — Application to Time Series Prediction with RBFN Models

Published:2003 Issue: Volume: Page:573-580
ISSN:0302-9743
Container-title:Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003
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Author:

Lendasse Amaury,Wertz Vincent,Verleysen Michel

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-44989-2_68

Reference11 articles.

1. Ljung, L.: System Identification-Theory for the user, 2nd ed, Prentice Hall, 1999.

2. Efron, B., Tibshirani, R. J. An introduction to the bootstrap, Chapman & Hall, 1993.

3. Efron, B, Tibshirani, R.: Improvements on cross-validation: The.632+ bootstrap method. J. Amer. Statist. Assoc. (1997) 92:548–560.

4. Stone, M.: An asymptotic equivalence of choice of model by cross-validation and Akaike’s criterion, J. Royal. Statist. Soc., B39, 44–7, 1977.

5. Kohavi, R.: A study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection, Proc. of the 14th Int. Joint Conf. on A.I., Vol. 2, Canada, 1995.

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