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.

Install the latest version of this package by entering the following in R:
install.packages("BCBCSF")
AuthorLonghai Li <longhai@math.usask.ca>
Date of publication2015-09-26 01:05:27
MaintainerLonghai Li <longhai@math.usask.ca>
LicenseGPL (>= 2)
Version1.0-1
http://www.r-project.org
http://math.usask.ca/~longhai

View on CRAN

Files

src
src/ccodes
src/ccodes/adjfactor.c
src/ccodes/pred.c
src/all.c
NAMESPACE
data
data/lymphoma.RData
R
R/tr-pr.r R/comp_pred.r
MD5
DESCRIPTION
man
man/evalpred.Rd man/analyzefit.Rd man/internal.Rd man/data.Rd man/example.Rd man/fitpred.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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