Package: agghoo 0.1-0

Benjamin Auder

agghoo: Aggregated Hold-Out Cross Validation

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) <arxiv:1909.04890> published in Journal of Machine Learning Research 22(20):1--55.

Authors:Sylvain Arlot [ctb], Benjamin Auder [aut, cre, cph], Melina Gallopin [ctb], Matthieu Lerasle [ctb], Guillaume Maillard [ctb]

agghoo_0.1-0.tar.gz
agghoo_0.1-0.zip(r-4.7-any)agghoo_0.1-0.zip(r-4.6-any)
agghoo_0.1-0.tar.gz(r-4.7-any)agghoo_0.1-0.tar.gz(r-4.6-any)
agghoo_0.1-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
agghoo/json (API)

# Install 'agghoo' in R:
install.packages('agghoo', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 1 scripts 312 downloads 9 exports 4 dependencies

Last updated from:fb4db45572. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK112
source / vignettesOK207
linux-releaseOK125
windows-develOK58
windows-releaseOK74
wasm-releaseOK104

Exports:agghooagghoo_runAgghooCVcompareMulticompareRangecompareToCVvoting_runModelstandardCV_run

Dependencies:classFNNR6rpart