cranhaven. To fix this you can add URL: https://cranhaven.r-universe.dev/agghoo to the package DESCRIPTION file. See also theR-universe documentation.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:
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.zip(r-4.5-any)
agghoo_0.1-0.tgz(r-4.6-any)agghoo_0.1-0.tgz(r-4.5-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://cranhaven.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues
Last updated from:4d44430315 (on package/agghoo). Checks:9 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 117 | ||
| source / vignettes | OK | 143 | ||
| linux-release | OK | 115 | ||
| macos-release | OK | 99 | ||
| macos-oldrel | OK | 93 | ||
| windows-devel | OK | 65 | ||
| windows-release | OK | 69 | ||
| windows-oldrel | OK | 60 | ||
| wasm-release | OK | 101 |
Exports:agghooagghoo_runAgghooCVcompareMulticompareRangecompareToCVvoting_runModelstandardCV_run
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| agghoo | agghoo |
| agghoo_run | agghoo_run |
| R6 class with agghoo functions fit() and predict(). | AgghooCV |
| compareMulti | compareMulti |
| compareRange | compareRange |
| compareTo | compareTo |
| CVvoting_run | CVvoting_run |
| R6 class representing a (generic) model. | Model |
| standardCV_run | standardCV_run |