Package: Rforestry 0.11.1.0

Theo Saarinen

Rforestry: Random Forests, Linear Trees, and Gradient Boosting for Inference and Interpretability

Provides fast implementations of Random Forests, Gradient Boosting, and Linear Random Forests, with an emphasis on inference and interpretability. Additionally contains methods for variable importance, out-of-bag prediction, regression monotonicity, and several methods for missing data imputation.

Authors:Sören Künzel [aut], Theo Saarinen [aut, cre], Simon Walter [aut], Sam Antonyan [aut], Edward Liu [aut], Allen Tang [aut], Jasjeet Sekhon [aut]

Rforestry_0.11.1.0.tar.gz
Rforestry_0.11.1.0.zip(r-4.7-x86_64)Rforestry_0.11.1.0.zip(r-4.7-arm64)Rforestry_0.11.1.0.zip(r-4.6-x86_64)Rforestry_0.11.1.0.zip(r-4.6-arm64)
Rforestry_0.11.1.0.tar.gz(r-4.7-arm64)Rforestry_0.11.1.0.tar.gz(r-4.7-x86_64)Rforestry_0.11.1.0.tar.gz(r-4.6-arm64)Rforestry_0.11.1.0.tar.gz(r-4.6-x86_64)
Rforestry_0.11.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
Rforestry/json (API)

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

Bug tracker:https://github.com/forestry-labs/rforestry/issues

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

On CRAN:

Conda:

openblascpp

2.60 score 80 scripts 362 downloads 16 exports 41 dependencies

Last updated from:499c585740. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK154
linux-devel-x86_64OK209
source / vignettesOK237
linux-release-arm64OK174
linux-release-x86_64OK201
windows-devel-arm64OK402
windows-devel-x86_64OK208
windows-release-arm64OK310
windows-release-x86_64OK149
wasm-releaseOK139

Exports:addTreesautoforestryautohonestRFcompute_lpCppToR_translatorforestrygetOOBgetOOBpredsgetVIhonestRFimpute_featuresloadForestrymake_savablemultilayerForestryrelinkCPP_prtsaveForestry

Dependencies:base64encbslibcachemclicodetoolsdigestevaluatefastmapfontawesomeforeachfsglmnethighrhtmltoolshtmlwidgetsiteratorsjquerylibjsonliteknitrlatticelifecyclemagrittrMatrixmemoisemimeonehotR6rappdirsRcppRcppArmadilloRcppEigenRcppThreadrlangrmarkdownsassshapesurvivaltinytexvisNetworkxfunyaml

Readme and manuals

Help Manual

Help pageTopics
addTrees-forestryaddTrees
autoforestry-forestryautoforestry
Honest Random ForestautohonestRF
compute lp distancescompute_lp compute_lp-forestry
Cpp to R translatorCppToR_translator
Checks if forestry object has valid pointer for C++ object.forest_checker
forestryforestry
forestry classforestry-class
getOOB-forestrygetOOB getOOB,forestry-method getOOB-forestry
getOOBpreds-forestrygetOOBpreds getOOBpreds-forestry
getVI-forestrygetVI
Honest Random ForesthonestRF
Feature imputation using random forests neigborhoodsimpute_features
load RFloadForestry
make_savablemake_savable make_savable,forestry-method
Multilayer forestrymultilayer-forestry multilayerForestry
visualize a treeplot-forestry plot.forestry
predict-forestrypredict-forestry predict.forestry
predict-multilayer-forestrypredict-multilayer-forestry predict.multilayerForestry
preprocess_testingpreprocess_testing
preprocess_trainingpreprocess_training
relink CPP ptrrelinkCPP_prt
save RFsaveForestry
Test data checktesting_data_checker testing_data_checker-forestry
Training data checktraining_data_checker