Package: forestControl 0.2.2

Tom Wilson

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) <arxiv:1410.2838>. Methods for calculating the selection frequency threshold at false positive rates and selection frequency false positive rate feature selection.

Authors:Tom Wilson [aut, cre], Jasen Finch [aut]

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forestControl.pdf |forestControl.html✨
forestControl/json (API)
NEWS

# Install 'forestControl' in R:
install.packages('forestControl', repos = c('https://aberhrml.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/aberhrml/forestcontrol/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

randomforest

4.00 score 2 stars 7 scripts 184 downloads 4 exports 18 dependencies

Last updated 3 years agofrom:4b9637c6df. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 12 2024
R-4.5-win-x86_64OKNov 12 2024
R-4.5-linux-x86_64OKNov 12 2024
R-4.4-win-x86_64OKNov 12 2024
R-4.4-mac-x86_64OKNov 12 2024
R-4.4-mac-aarch64OKNov 12 2024
R-4.3-win-x86_64OKNov 12 2024
R-4.3-mac-x86_64OKNov 12 2024
R-4.3-mac-aarch64OKNov 12 2024

Exports:extract_paramsfpr_fsselection_freqssft

Dependencies:clidplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigpurrrR6Rcpprlangtibbletidyselectutf8vctrswithr

Getting Started

Rendered fromGetting_started.Rmdusingknitr::rmarkdownon Nov 12 2024.

Last update: 2021-09-22
Started: 2021-09-22