Dimension Reduction for Classification with Gene Expression Microarray Data

DOI10.2202/1544-6115.1147zbMath1166.62337OpenAlexW2113847750WikidataQ31038661 ScholiaQ31038661MaRDI QIDQ5442979

David M. Rocke, Linh H. Lieu, Jianjian Dai

Publication date: 18 February 2008

Published in: Statistical Applications in Genetics and Molecular Biology (Search for Journal in Brave)

Full work available at URL: http://www.bepress.com/sagmb/vol5/iss1/art6

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40)

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Influence functions for linear discriminant analysis: sensitivity analysis and efficient influence diagnostics ⋮ Ensemble of penalized logistic models for classification of high-dimensional data ⋮ Optimal discriminant analysis in high-dimensional latent factor models ⋮ Bayesian classification for bivariate normal gene expression ⋮ Methods for pattern selection, class-specific feature selection and classification for automated learning ⋮ Partial least squares classification for high dimensional data using the PCOUT algorithm ⋮ Bias-Corrected Diagonal Discriminant Rules for High-Dimensional Classification ⋮ Orthogonal joint sparse NMF for microarray data analysis ⋮ Overlapping sliced inverse regression for dimension reduction ⋮ Fuzzy Patterns and GCS Networks to Clustering Gene Expression Data

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