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agghoo  

Aggregated Hold-Out Cross Validation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("agghoo", "0.1-0")



Attach the package and use:
library("agghoo")
Maintained by
Benjamin Auder
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-05-25
Latest Update: 2023-05-25
Description:
The 'agghoo' procedure is an alternative to usual cross-validation. Instead of choosing the best model trained on V subsamples, it determines a winner model for each subsample, and then aggregates the V outputs. For the details, see "Aggregated hold-out" by Guillaume Maillard, Sylvain Arlot, Matthieu Lerasle (2021) published in Journal of Machine Learning Research 22(20):1--55.
How to cite:
Benjamin Auder (2023). agghoo: Aggregated Hold-Out Cross Validation. R package version 0.1-0, https://cran.r-project.org/web/packages/agghoo. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-09-15 08:25), 0.1-0 (2023-05-25 21:50)
Other packages that cited agghoo R package
View agghoo citation profile
Other R packages that agghoo depends, imports, suggests or enhances
Complete documentation for agghoo
Functions, R codes and Examples using the agghoo R package
Some associated functions: AgghooCV . CVvoting_run . Model . agghoo . agghoo_run . compareMulti . compareRange . compareTo . standardCV_run . 
Some associated R codes: R6_AgghooCV.R . R6_Model.R . agghoo.R . checks.R . compareTo.R . utils.R .  Full agghoo package functions and examples
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