Package: randomPlantedForest 0.2.1.9000

Lukas Burk

randomPlantedForest: Random Planted Forest: A Directly Interpretable Tree Ensemble

An implementation of the Random Planted Forest algorithm for directly interpretable tree ensembles based on a functional ANOVA decomposition.

Authors:Joseph Theo Meyer [aut], Munir Hiabu [aut], Maike Spankus [aut], Marvin N. Wright [aut], Lukas Burk [cre, aut]

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

# Install 'randomPlantedForest' in R:

install.packages('randomPlantedForest', repos = c('https://plantedml.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/plantedml/randomplantedforest/issues

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

intelligibility interpretable-machine-learning interpretable-ml machine-learning ml random-forest

4.23 score 3 stars 38 scripts 4 exports 16 dependencies

Last updated 14 days agofrom:41fe7eef99. Checks:OK: 6 NOTE: 3. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 04 2024
R-4.5-win-x86_64	OK	Nov 04 2024
R-4.5-linux-x86_64	OK	Nov 04 2024
R-4.4-win-x86_64	NOTE	Nov 04 2024
R-4.4-mac-x86_64	NOTE	Nov 04 2024
R-4.4-mac-aarch64	NOTE	Nov 04 2024
R-4.3-win-x86_64	OK	Nov 04 2024
R-4.3-mac-x86_64	OK	Nov 04 2024
R-4.3-mac-aarch64	OK	Nov 04 2024

Exports:is_purified predict_components purify rpf

Dependencies:backports checkmate cli data.table fansi glue hardhat lifecycle magrittr pillar pkgconfig Rcpp rlang tibble utf8 vctrs

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Extract predicted components from a Random Planted Forest	predict_components
Random Planted Forest Predictions	predict.rpf
Print an rpf fit	print.rpf
Compact printing of forest structures	print.rpf_forest str.rpf_forest
Purify a Random Planted Forest	is_purified purify purify.default purify.rpf
Random Planted Forest	rpf rpf.data.frame rpf.formula rpf.matrix rpf.recipe

Usage by other packages (reverse dependencies)