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+Package: agghoo
+Title: Aggregated Hold-Out Cross Validation
+Date: 2022-08-30
+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: class, parallel, R6, rpart, FNN
+Suggests: roxygen2
+URL: https://git.auder.net/?p=agghoo.git
+License: MIT + file LICENSE
+RoxygenNote: 7.2.1
+Collate: 'compareTo.R' 'agghoo.R' 'R6_AgghooCV.R' 'R6_Model.R'
+        'checks.R' 'utils.R' 'A_NAMESPACE.R'
+NeedsCompilation: no
+Packaged: 2022-09-09 15:45:56 UTC; auder