SelectBoost
A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets
An implementation of the selectboost algorithm (Bertrand et al. 2020, 'Bioinformatics', doi:10.1093/bioinformatics/btaa855), which is a general algorithm that improves the precision of any existing variable selection method. This algorithm is based on highly intensive simulations and takes into account the correlation structure of the data. It can either produce a confidence index for variable selection or it can be used in an experimental design planning perspective.
- Version2.2.2
- R version≥ 2.10
- LicenseGPL-3
- Needs compilation?No
- SelectBoost citation info
- Last release11/30/2022
Documentation
Team
Frederic Bertrand
MaintainerShow author detailsMyriam Maumy-Bertrand
Nicolas Jung
Show author detailsRolesContributorIsmail Aouadi
Show author detailsRolesContributor
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- Imports9 packages
- Suggests4 packages
- Reverse Imports1 package