Fully Bayesian Classification with a subset of highdimensional features, such as expression levels of genes. The data are modeled with a hierarchical Bayesian models using heavytailed 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 bettercalibrated predictions for future cases when one uses Fstatistic to select features.
Package details 


Author  Longhai Li <longhai@math.usask.ca> 
Maintainer  Longhai Li <longhai@math.usask.ca> 
License  GPL (>= 2) 
Version  1.01 
URL  http://www.rproject.org http://math.usask.ca/~longhai 
Package repository  View on CRAN 
Installation 
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