comp_amlp

comp_eer

comp_loss

gen_qflmd

mcmc_pred

met_gauss

mk_folds

mlepred

probs_attrue

rank_F

richisq

rinvgam

trpr_mle

log_sum_exp

comp_adjfactor

This function is internal. Type the function name to look at its details

internal

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.

Longhai Li

BCBCSF

Bias-Corrected Bayesian Classification with Selected Features

internal function

Internal functions used in package `gausspred'

internal: Internal functions used in package `gausspred'

Description

Arguments