Estimation of misclassification probabilities by bootstrap methods

1 January 1983

journal article
research article
Published by Taylor & Francis in Communications in Statistics - Simulation and Computation

Vol. 12 (6) , 645-656
https://doi.org/10.1080/03610918308812350

Abstract

Several methods have been proposed to estimate the misclassification probabilities when a linear discriminant function is used to classify an observation into one of several populations. We describe the application of bootstrap sampling to the above problem. The proposed method has the advantage of not only furnishing the estimates of misclassification probabilities but also provides an estimate of the standard error of estimate. The method is illustrated by a small simulation experiment. It is then applied to three published, well accessible data sets, which are typical of large, medium and small data sets encountered in practice.

Keywords

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