A comparison of regularization methods applied to the linear discriminant function with high-dimensional microarray data

DOI10.1080/00949655.2011.625946zbMath1367.62299OpenAlexW1983005403MaRDI QIDQ4922655

John A. Ramey, Phil D. Young

Publication date: 3 June 2013

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2011.625946

zbMATH Keywords

microarray datalinear discriminant analysisexpected error ratecovariance-matrix regularizationhigh-dimensional supervised classification

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Uses Software

• ggplot2

Cites Work

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• Expected classification error of the Fisher linear classifier with pseudo-inverse covariance matrix
• Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data
• Selection bias in gene extraction on the basis of microarray gene-expression data
• Comparison of Discrimination Methods for High Dimensional Data
• Shrinkage‐based Diagonal Discriminant Analysis and Its Applications in High‐Dimensional Data

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