Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation
Journal of the American Statistical AssociationPublished 1 June 1983
Bradley Efron
Citations2,161
SJR quartileQ1
SJR score4.10
SNIP3.08
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Abstract
Abstract We construct a prediction rule on the basis of some data, and then wish to estimate the error rate of this rule in classifying future observations. Cross-validation provides a nearly unbiased estimate, using only the original data. Cross-validation turns out to be related closely to the bootstrap estimate of the error rate. This article has two purposes: to understand better the theoretical basis of the prediction problem, and to investigate some related estimators, which seem to offer considerably improved estimation in small samples.
Keywords
MathematicsDecision Sciences
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