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

v1v2v3v4 (latest)

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"

5 / 5 papers shown

i-Razor: A Differentiable Neural Input Razor for Feature Selection and
Dimension Search in DNN-Based Recommender Systems

i-Razor: A Differentiable Neural Input Razor for Feature Selection and Dimension Search in DNN-Based Recommender SystemsIEEE Transactions on Knowledge and Data Engineering (TKDE), 2022

170

4

0

01 Apr 2022

Nested cross-validation when selecting classifiers is overzealous for
most practical applications

Nested cross-validation when selecting classifiers is overzealous for most practical applicationsExpert systems with applications (ESWA), 2018

268

265

0

25 Sep 2018

Optimal whitening and decorrelation

Optimal whitening and decorrelation

360

489

0

02 Dec 2015

Sparse Proteomics Analysis - A compressed sensing-based approach for
feature selection and classification of high-dimensional proteomics mass
spectrometry data

Sparse Proteomics Analysis - A compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry dataBMC Bioinformatics (BMC Bioinformatics), 2015

Christof Schütte

301

35

0

11 Jun 2015

Higher Criticism for Large-Scale Inference, Especially for Rare and Weak
Effects

Higher Criticism for Large-Scale Inference, Especially for Rare and Weak Effects

337

141

0

17 Oct 2014

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