Bias-Corrected Bayesian Classification with Selected Features
Functions for analyzing and visualizing a BCBCSF fitting result
Lymphoma Microarray Data
A function for evaluating arrays of predictive probabilities with the ...
Examples of fitting models, predicting class labels, evaluating predic...
Functions for fitting models with MCMC, predicting class labels of tes...
Internal functions used in package `gausspred'
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.