Classification and feature gene selection using the normalized maximum likelihood model for discrete regression

DOI10.1016/S0165-1684(02)00470-XzbMath1144.62360MaRDI QIDQ947399

Ioan Tabus, Jorma Rissanen, Jaakko T. Astola

Publication date: 2 October 2008

Published in: Signal Processing (Search for Journal in Brave)

zbMATH Keywords

classificationminimum description lengthfeature selectiongene expressionnormalized maximum likelihooddiscrete regression

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) General nonlinear regression (62J02) Biochemistry, molecular biology (92C40) Genetics and epigenetics (92D10)

Related Items (2)

NONLINEAR PROBIT GENE CLASSIFICATION USING MUTUAL INFORMATION AND WAVELET-BASED FEATURE SELECTION ⋮ GENE SELECTION USING LOGISTIC REGRESSIONS BASED ON AIC, BIC AND MDL CRITERIA

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