BCBCSF: Bias-Corrected Bayesian Classification with Selected Features

Fully Bayesian Classification with a subset of high-dimensional features, such as expression levels of genes. The data are modeled with a hierarchical Bayesian models using heavy-tailed t distributions as priors. When a large number of features are available, one may like to select only a subset of features to use, typically those features strongly correlated with the response in training cases. Such a feature selection procedure is however invalid since the relationship between the response and the features has be exaggerated by feature selection. This package provides a way to avoid this bias and yield better-calibrated predictions for future cases when one uses F-statistic to select features.

Getting started

Package details

AuthorLonghai Li <longhai@math.usask.ca>
MaintainerLonghai Li <longhai@math.usask.ca>
LicenseGPL (>= 2)
URL http://www.r-project.org http://math.usask.ca/~longhai
Package repositoryView on CRAN
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BCBCSF documentation built on May 2, 2019, 1:08 p.m.