Bayesian binary kernel probit model for microarray based cancer classification and gene selection

DOI10.1016/j.csda.2009.05.007zbMath1453.62061OpenAlexW2094789795MaRDI QIDQ961916

Sounak Chakraborty

Publication date: 1 April 2010

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

Full work available at URL: https://doi.org/10.1016/j.csda.2009.05.007

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)

Related Items (8)

Bayesian variable selection with sparse and correlation priors for high-dimensional data analysis ⋮ An efficient sampling algorithm with adaptations for Bayesian variable selection ⋮ A Bayesian hybrid huberized support vector machine and its applications in high-dimensional medical data ⋮ A Bayesian approach to model-based clustering for binary panel probit models ⋮ Functional gradient ascent for probit regression ⋮ Bayesian semi-supervised learning with support vector machine ⋮ Bayesian Approximate Kernel Regression With Variable Selection ⋮ Sparse bayesian kernel multinomial probit regression model for high-dimensional data classification

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