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JOUSBoost  

Implements Under/Oversampling for Probability Estimation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("JOUSBoost", "2.1.0")



Attach the package and use:
library("JOUSBoost")
Maintained by
Matthew Olson
[Scholar Profile | Author Map]
First Published: 2016-09-12
Latest Update: 2017-07-12
Description:
Implements under/oversampling for probability estimation. To be used with machine learning methods such as AdaBoost, random forests, etc.
How to cite:
Matthew Olson (2016). JOUSBoost: Implements Under/Oversampling for Probability Estimation. R package version 2.1.0, https://cran.r-project.org/web/packages/JOUSBoost. Accessed 13 Apr. 2025.
Previous versions and publish date:
1.0.0 (2016-09-12 20:55), 2.0.0 (2017-05-23 19:25)
Other packages that cited JOUSBoost R package
View JOUSBoost citation profile
Other R packages that JOUSBoost depends, imports, suggests or enhances
Complete documentation for JOUSBoost
Functions, R codes and Examples using the JOUSBoost R package
Some associated functions: JOUSBoost . adaboost . circle_data . friedman_data . grid_probs . index_over . index_under . jous . predict.adaboost . predict.jous . print.adaboost . print.jous . sonar . 
Some associated R codes: JOUSBoost.R . RcppExports.R . adaboost.R . jous.R . jous_utility.R . simulation.R . zzz.R .  Full JOUSBoost package functions and examples
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