A survey of cross-validation procedures for model selection

Abstract : Used to estimate the risk of an estimator or to perform model selection, cross-validation is a widespread strategy because of its simplicity and its apparent universality. Many results exist on the model selection performances of cross-validation procedures. This survey intends to relate these results to the most recent advances of model selection theory, with a particular emphasis on distinguishing empirical statements from rigorous theoretical results. As a conclusion, guidelines are provided for choosing the best cross-validation procedure according to the particular features of the problem in hand.
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Article dans une revue
Statistics Surveys, Institute of Mathematical Statistics (IMS), 2010, 4, pp.40--79. <10.1214/09-SS054>
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Dernière modification le : jeudi 29 septembre 2016 - 01:05:12
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Sylvain Arlot, Alain Celisse. A survey of cross-validation procedures for model selection. Statistics Surveys, Institute of Mathematical Statistics (IMS), 2010, 4, pp.40--79. <10.1214/09-SS054>. <hal-00407906>

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