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.

Version: 1.0-1
Depends: R (≥ 2.13.1), abind
Published: 2015-09-26
Author: Longhai Li
Maintainer: Longhai Li <longhai at math.usask.ca>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.r-project.org, http://math.usask.ca/~longhai
NeedsCompilation: yes
In views: Bayesian
CRAN checks: BCBCSF results

Documentation:

Reference manual: BCBCSF.pdf

Downloads:

Package source: BCBCSF_1.0-1.tar.gz
Windows binaries: r-devel: BCBCSF_1.0-1.zip, r-release: BCBCSF_1.0-1.zip, r-oldrel: BCBCSF_1.0-1.zip
macOS binaries: r-release (arm64): BCBCSF_1.0-1.tgz, r-oldrel (arm64): BCBCSF_1.0-1.tgz, r-release (x86_64): BCBCSF_1.0-1.tgz
Old sources: BCBCSF archive

Reverse dependencies:

Reverse imports: HTLR

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