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agghoo
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]
[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 21 Nov. 2024.
Previous versions and publish date:
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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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