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- W2054667069 abstract "In this paper we present a simulation study for comparing differents methods for estimating the prediction error rate in a discrimination problem. We consider the Cross-validation, Bootstrap and Bayesian Bootstrap methods for such as problem, while also elaborating on both simple and Bayesian Bootstrap methods by smoothing techniques. We observe as the smoothing procedure lead to improvements in the estimation of the true error rate of the discrimination rule, specially in the case of the smooth Bayesian Bootstrap estimator, whose reduction in M.S.E. resulted from the high positive correlation between the true error rate and its estimations based in this method." @default.
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- W2054667069 date "1989-01-01" @default.
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- W2054667069 title "The use of Smooth Bootstrap Techniques for Estimating the Error Rate of a Prediction Rule" @default.
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- W2054667069 doi "https://doi.org/10.1080/03610918908812812" @default.
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