Bias-Corrected Bayesian Classification with Selected Features
Overview
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.
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- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-04-05
- NOTE8 OK, 6 NOTE2026-03-10
Documentation
- Help pages
- 6 (1 internal)
- Examples that run
- 50%1 run in a plain check · 1 never run
- Exported functions with examples
- 50%
- Documented parameters
- 63%
- Return-value docs
- 100%
- Help pages citing references
- 17%
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- Claude Codefirst seen 2026-08-18Commits: 11 by its own account · at least 18 crediting it in the message
- Claude Sonnet 510 commits · Aug to Oct 2026
- Claude Opus 5.57 commits · Sep to Oct 2026
- Claude Sonnet 5.51 commit · Sep 2026
Dependencies
Installing BCBCSF adds 1 package (0 with compiled code, 21 KB of source tarballs). Heaviest: abind 21 KB.
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- RR 3.2.0 released · 2015-04-16
- RR 3.1.0 released · 2014-04-10
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Package metadata
- First published
- 2011-07-27
- Total releases
- 6 / 15 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 2.13.1
- Bundled data
- 637 KB / 1 file
- Download size
- 655 KB
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