Package: optRF 1.1.0

optRF: Optimising Random Forest Stability by Determining the Optimal Number of Trees

Calculating the stability of random forest with certain numbers of trees. The non-linear relationship between stability and numbers of trees is described using a logistic regression model and used to estimate the optimal number of trees.

Authors:Thomas Martin Lange [cre, aut], Felix Heinrich [ctb]

optRF_1.1.0.tar.gz
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optRF.pdf |optRF.html✨
optRF/json (API)
NEWS

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

Bug tracker:https://github.com/tmlange/optrf/issues

Datasets:
  • SNPdata - Simulated data of wheat yield and genomic markers

On CRAN:

Conda-Forge:

4.78 score 562 downloads 5 exports 8 dependencies

Last updated 1 months agofrom:50d66d9706. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-winOKMar 06 2025
R-4.5-macOKMar 06 2025
R-4.5-linuxOKMar 06 2025
R-4.4-winOKMar 06 2025
R-4.4-macOKMar 06 2025
R-4.4-linuxOKMar 06 2025
R-4.3-winOKMar 06 2025
R-4.3-macOKMar 06 2025

Exports:estimate_numtreesestimate_stabilityopt_importanceopt_predictionplot_stability

Dependencies:irrlatticelpSolveMatrixminpack.lmrangerRcppRcppEigen

Optimising random forest for prediction based decision-making processes

Rendered fromopt_prediction.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2025-02-01
Started: 2025-01-31

Optimising random forest for variable selection

Rendered fromopt_importance.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2025-02-01
Started: 2025-01-31

Optimising random forest using optRF

Rendered fromoptRF.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2025-02-01
Started: 2025-01-31