JOUSBoost: Implements Under/Oversampling for Probability Estimation

Implements under/oversampling for probability estimation. To be used with machine learning methods such as AdaBoost, random forests, etc.

Version: 2.1.0
Depends: R (≥ 2.10)
Imports: Rcpp, rpart, stats, doParallel, foreach
LinkingTo: Rcpp
Suggests: testthat, knitr, rmarkdown
Published: 2017-07-12
Author: Matthew Olson [aut, cre]
Maintainer: Matthew Olson <maolson at wharton.upenn.edu>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README
CRAN checks: JOUSBoost results

Documentation:

Reference manual: JOUSBoost.pdf
Vignettes: JOUSBoost

Downloads:

Package source: JOUSBoost_2.1.0.tar.gz
Windows binaries: r-devel: JOUSBoost_2.1.0.zip, r-release: JOUSBoost_2.1.0.zip, r-oldrel: JOUSBoost_2.1.0.zip
macOS binaries: r-release (arm64): JOUSBoost_2.1.0.tgz, r-oldrel (arm64): JOUSBoost_2.1.0.tgz, r-release (x86_64): JOUSBoost_2.1.0.tgz
Old sources: JOUSBoost archive

Reverse dependencies:

Reverse suggests: qeML

Linking:

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