Fast approximation of the bootstrap for model selection
نویسندگان
چکیده
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 difficulty associated with the bootstrap in real-world applications is the high computation load. In this paper we propose a simple procedure based on empirical evidence, to considerably reduce the computation time needed to estimate the generalization error of a family of models of increasing number of parameters.
منابع مشابه
Fast bootstrap methodology for regression model selection
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