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A bias-variance trade-off in the prediction error estimation behavior in bootstrap methods for microarray leukemia classification
2018
Journal of biostatistics and epidemiology
& Aim: The bootstrap is a method that resample from the original data set. There are the wide ranges of bootstrap application for estimating the prediction error rate. We compare some bootstrap methods for estimating prediction error in classification and choose the best method for the microarray leukemia classification. Methods & Materials: The sample consist of n=38 patients with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) with p=4120 genes that n<<p from an existing
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