Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation

作者: Bradley Efron

DOI: 10.1080/01621459.1983.10477973

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摘要: Abstract We construct a prediction rule on the basis of some data, and then wish to estimate error rate this in classifying future observations. Cross-validation provides nearly unbiased estimate, using only original data. turns out be related closely bootstrap rate. This article has two purposes: understand better theoretical problem, investigate estimators, which seem offer considerably improved estimation small samples.

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