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SelectBoost  

A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets
View on CRAN: Click here


Download and install SelectBoost package within the R console
Install from CRAN:
install.packages("SelectBoost")

Install from Github:
library("remotes")
install_github("cran/SelectBoost")

Install by package version:
library("remotes")
install_version("SelectBoost", "2.2.2")



Attach the package and use:
library("SelectBoost")
Maintained by
Frederic Bertrand
[Scholar Profile | Author Map]
First Published: 2019-05-27
Latest Update: 2022-11-30
Description:
An implementation of the selectboost algorithm (Bertrand et al. 2020, 'Bioinformatics', ), 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.
How to cite:
Frederic Bertrand (2019). SelectBoost: A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets. R package version 2.2.2, https://cran.r-project.org/web/packages/SelectBoost. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.4.0 (2019-05-27 11:20), 2.0.0 (2020-02-23 14:30), 2.2.0 (2021-03-20 22:10), 2.2.1 (2022-11-29 22:10)
Other packages that cited SelectBoost R package
View SelectBoost citation profile
Other R packages that SelectBoost depends, imports, suggests or enhances
Complete documentation for SelectBoost
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