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Feature selection in omics prediction problems using cat scores and false nondiscovery rate control
11 March 2009
M. Ahdesmaki
K. Strimmer
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Papers citing
"Feature selection in omics prediction problems using cat scores and false nondiscovery rate control"
4 / 4 papers shown
Title
Nested cross-validation when selecting classifiers is overzealous for most practical applications
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G. Cawley
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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
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