Aggregated Hold-Out Cross Validation R package agghoo version 0.1-0 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. Software Depends: R (>= 3.5.0) Imports: class, parallel, R6, rpart, FNN Suggests: roxygen2, mlbench Benjamin Auder <benjamin.auder@universite-paris-saclay.fr> Comprehensive R Archive Network (CRAN) Sylvain Arlot [ctb], Benjamin Auder [aut, cre, cph], Melina Gallopin [ctb], Matthieu Lerasle [ctb], Guillaume Maillard [ctb] MIT + file LICENSE (https://CRAN.R-project.org/package=agghoo/LICENSE) 2023-05-25 application/tgz https://CRAN.R-project.org/package=agghoo doi:10.32614/CRAN.package.agghoo