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Estimating misclassification error: a closer look at cross-validation based methods

BACKGROUND: To estimate a classifier’s error in predicting future observations, bootstrap methods have been proposed as reduced-variation alternatives to traditional cross-validation (CV) methods based on sampling without replacement. Monte Carlo (MC) simulation studies aimed at estimating the true...

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Библиографические подробности
Главные авторы: Ounpraseuth, Songthip, Lensing, Shelly Y, Spencer, Horace J, Kodell, Ralph L
Формат: Artigo
Язык:Inglês
Опубликовано: BioMed Central 2012
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Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC3556102/
https://ncbi.nlm.nih.gov/pubmed/23190936
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1756-0500-5-656
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