Unbiased estimate of generalization error and model selection in neural network

@article{Liu1995UnbiasedEO,
  title={Unbiased estimate of generalization error and model selection in neural network},
  author={Yong Liu},
  journal={Neural Networks},
  year={1995},
  volume={8},
  pages={215-219}
}
-Model selection is based upon the generalization errors of the models in consideration. To estimate the generalization error of a model from the training data, the method of cross-validation and the asymptotic form of the jackknife estimator are used. The average of the predictive errors is used to estimate the generalization error. This estimate is also used as the model selection criterion. The asymptotic form of this estimate is obtained. Asymptotic model selection criterion is also… CONTINUE READING
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