BCBCSF (1.0-0)

0 users

Bias-corrected Bayesian Classification with Selected Features.

http://www.r-project.org
http://math.usask.ca/~longhai
http://cran.r-project.org/web/packages/BCBCSF

This package is used to predict the discrete class labels based on a selected 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.

Maintainer: Longhai Li
Author(s): Longhai Li <longhai@math.usask.ca>

License: GPL (>= 2)

Uses: abind

Released 4 months ago.

3 previous versions

Ratings

Overall:
  (0 votes)

Documentation:
  (0 votes)

Log in to vote.

Reviews

No one has written a review of BCBCSF yet. Want to be the first? Write one now.

Related packages: BACCO, BMA, BayHaz, BayesTree, BayesValidate, Bolstad, DPpackage, EbayesThresh, HI, Hmisc, LearnBayes, MCMCpack, MNP, MSBVAR, MasterBayes, R2WinBUGS, RJaCGH, arm, bayesSurv, bayesm … (20 best matches, based on common tags.)

Search for BCBCSF on google, google scholar, r-help, r-devel.

Visit BCBCSF on R Graphical Manual.