A survey of cross-validation procedures for model selection
A survey of cross-validation procedures for model selection
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DOI：
10.1214/09-ss054
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发表时间：
2010-01-01
影响因子：
3.3
通讯作者：
Celisse, Alain
中科院分区：
文献类型：
--
作者：
Arlot, Sylvain;Celisse, Alain
交叉验证用于估计估计者的风险或进行模型选择，由于其简单性和(明显的)普遍性，它是一种广泛使用的策略。关于交叉验证过程的模型选择性能，已有很多结果。这项调查旨在将这些结果与模型选择理论的最新进展联系起来，特别强调区分经验陈述和严格的理论结果。作为结论，提供了根据手头问题的具体特点选择最佳交叉验证程序的指导方针。
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.