Classification rule based on Bayesian naive Bayes models with feature selection bias corrected: This software is used to predict the binary response based on high dimensional features, for example gene expression data. The data are modelled with Bayesian naive Bayes models. 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 will appear stronger. This package provides a way to avoid this bias and yields well-calibrated prediction for the test cases.
- Changes to previous version:
Fetched by r-cran-robot on 2012-12-01 00:00:07.510624
No one has posted any comments yet. Perhaps you'd like to be the first?
Leave a comment
You must be logged in to post comments.