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Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation
Journal of the American Statistical Association
Vol. 78, No. 382 (Jun., 1983), pp. 316-331
Stable URL: http://www.jstor.org/stable/2288636
Page Count: 16
You can always find the topics here!Topics: Error rates, Estimators, Statistical estimation, Estimation bias, Maximum likelihood estimation, Experimentation, Estimation methods, Gongs, Mathematical vectors, Random variables
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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.
Journal of the American Statistical Association © 1983 American Statistical Association