Feature selection in omics prediction problems using cat scores and
false nondiscovery rate control

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Feature selection in omics prediction problems using cat scores and false nondiscovery rate control

11 March 2009

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Papers citing "Feature selection in omics prediction problems using cat scores and false nondiscovery rate control"

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Title
Nested cross-validation when selecting classifiers is overzealous for most practical applications Jacques Wainer G. Cawley 55 216 0 25 Sep 2018
Optimal whitening and decorrelation A. Kessy A. Lewin K. Strimmer 97 405 0 02 Dec 2015
Sparse Proteomics Analysis - A compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data Tim Conrad Martin Genzel Nada Cvetkovic Niklas Wulkow A. Leichtle J. Vybíral Gitta Kutyniok Christof Schütte 13 34 0 11 Jun 2015
Higher Criticism for Large-Scale Inference, Especially for Rare and Weak Effects D. Donoho Jiashun Jin 122 131 0 17 Oct 2014