On the Influence of Input Noise on a Generalization Error Estimator

Abstract

Estimating the generalization capability is one of the most important problems in supervised learning. Therefore, various generalization error estimators have been proposed so far, in the presence of noise in output values. On the other hand, noise often exists in input values as well as output values. In this paper, we therefore investigate the influence… (More)

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Cite this paper

@inproceedings{Sugiyama2004OnTI, title={On the Influence of Input Noise on a Generalization Error Estimator}, author={Masashi Sugiyama and Yuta Okabe and Hidemitsu Ogawa}, year={2004} }