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forestControl: Approximate False Positive Rate Control in Selection Frequency
for Random Forest
Approximate false positive rate control in selection frequency for
random forest using the methods described by Ender Konukoglu and Melanie Ganz (2014) <doi:10.48550/arXiv.1410.2838>.
Methods for calculating the selection frequency threshold at false positive rates
and selection frequency false positive rate feature selection.
| Version: |
0.2.2 |
| Imports: |
Rcpp, purrr, tibble, magrittr, dplyr |
| LinkingTo: |
Rcpp |
| Suggests: |
testthat, randomForest, ranger, parsnip, knitr, rmarkdown |
| Published: |
2022-02-09 |
| DOI: |
10.32614/CRAN.package.forestControl |
| Author: |
Tom Wilson  [aut,
cre],
Jasen Finch [aut] |
| Maintainer: |
Tom Wilson <tpw2 at aber.ac.uk> |
| BugReports: |
https://github.com/aberHRML/forestControl/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/aberHRML/forestControl |
| NeedsCompilation: |
yes |
| Citation: |
forestControl citation info |
| Materials: |
NEWS |
| CRAN checks: |
forestControl results |
Documentation:
Downloads:
Linking:
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https://CRAN.R-project.org/package=forestControl
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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