Package: agghoo
Title: Aggregated Hold-out Cross Validation
Date: 2021-06-05
Version: 0.1-0
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 aggregate 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.
Author: Sylvain Arlot <sylvain.arlot@universite-paris-saclay.fr> [cph,ctb],
    Benjamin Auder <benjamin.auder@universite-paris-saclay.fr> [aut,cre,cph],
    Melina Gallopin <melina.gallopin@universite-paris-saclay.fr> [cph,ctb],
    Matthieu Lerasle <matthieu.lerasle@universite-paris-saclay.fr> [cph,ctb],
    Guillaume Maillard <guillaume.maillard@uni.lu> [cph,ctb]
Maintainer: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr>
Depends:
    R (>= 3.5.0)
Imports:
    R6,
    caret,
    rpart,
    randomForest,
    FNN
Suggests:
    roxygen2
URL: https://git.auder.net/?p=agghoo.git
License: MIT + file LICENSE
RoxygenNote: 7.1.1
Collate: 
    'agghoo.R'
    'R6_AgghooCV.R'
    'R6_Model.R'
    'A_NAMESPACE.R'