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]

forestControl_0.2.2.tar.gz
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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'))

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

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

On CRAN:

randomforestcpp

4.00 score 2 stars 7 scripts 238 downloads 4 exports 18 dependencies

Last updated 3 years agofrom:4b9637c6df. Checks:11 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 10 2025
R-4.5-win-x86_64OKFeb 10 2025
R-4.5-mac-x86_64OKFeb 10 2025
R-4.5-mac-aarch64OKFeb 10 2025
R-4.5-linux-x86_64OKFeb 10 2025
R-4.4-win-x86_64OKFeb 10 2025
R-4.4-mac-x86_64OKFeb 10 2025
R-4.4-mac-aarch64OKFeb 10 2025
R-4.3-win-x86_64OKFeb 10 2025
R-4.3-mac-x86_64OKFeb 10 2025
R-4.3-mac-aarch64OKFeb 10 2025

Exports:extract_paramsfpr_fsselection_freqssft

Dependencies:clidplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigpurrrR6Rcpprlangtibbletidyselectutf8vctrswithr

Getting Started

Rendered fromGetting_started.Rmdusingknitr::rmarkdownon Feb 10 2025.

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