A survey of cross-validation procedures for model selection

作者：Sylvain Arlot, Alain Celisse · 发表于：Statistics Surveys · 年份：2010 · DOI：10.1214/09-ss054 · 被引用次数：3406 · 研究领域：Statistical Methods and Inference、Statistical Methods and Bayesian Inference、Advanced Statistical Methods and Models

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 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.