High-dimensional pseudo-logistic regression and classification with applications to gene expression data

DOI10.1016/j.csda.2006.12.033zbMath1452.62554OpenAlexW2079656278MaRDI QIDQ1020833

Chunming Zhang, Haoda Fu, Tao Yu, Yuan Jiang

Publication date: 2 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.12.033

zbMATH Keywords

loss functionlogistic regressionsupport vector machineBayes optimal rulelarge \(p\) and small \(n\) data

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Generalized linear models (logistic models) (62J12) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

Adaptive clustering for time series: application for identifying cell cycle expressed genes ⋮ Editorial: Statistical genetics \& statistical genomics: where biology, epistemology, statistics, and computation collide ⋮ Editorial: Statistical learning methods including dimensionality reduction

Uses Software

• alr3

Cites Work

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