Package: randomForest 4.7-1.2

randomForest: Breiman and Cutlers Random Forests for Classification and Regression

Classification and regression based on a forest of trees using random inputs, based on Breiman (2001) <doi:10.1023/A:1010933404324>.

Authors:Leo Breiman [aut], Adele Cutler [aut], Andy Liaw [aut, cre], Matthew Wiener [aut]

randomForest_4.7-1.2.tar.gz
randomForest_4.7-1.2.zip(r-4.7)randomForest_4.7-1.2.zip(r-4.6)randomForest_4.7-1.2.zip(r-4.5)
randomForest_4.7-1.2.tgz(r-4.6-x86_64)randomForest_4.7-1.2.tgz(r-4.6-arm64)randomForest_4.7-1.2.tgz(r-4.5-x86_64)randomForest_4.7-1.2.tgz(r-4.5-arm64)
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randomForest_4.7-1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
randomForest/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

12.46 score 52 stars 298 packages 51k scripts 122k downloads 1.4k mentions 18 exports 0 dependencies

Last updated from:0ad64d71e8. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK122
linux-devel-x86_64OK105
source / vignettesOK140
linux-release-arm64OK114
linux-release-x86_64OK109
macos-release-arm64OK92
macos-release-x86_64OK184
macos-oldrel-arm64OK111
macos-oldrel-x86_64OK182
windows-develOK78
windows-releaseOK73
windows-oldrelOK87
wasm-releaseOK84

Exports:classCentercombinegetTreegrowimportancemarginMDSplotna.roughfixoutlierpartialPlotrandomForestrfcvrfImputerfNewstreesizetuneRFvarImpPlotvarUsed

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Prototypes of groups.classCenter
Combine Ensembles of Treescombine
Extract a single tree from a forest.getTree
Add trees to an ensemblegrow grow.default grow.randomForest
Extract variable importance measureimportance importance.default importance.randomForest
The Automobile Dataimports85
Margins of randomForest Classifiermargin margin.default margin.randomForest plot.margin
Multi-dimensional Scaling Plot of Proximity matrix from randomForestMDSplot
Rough Imputation of Missing Valuesna.roughfix na.roughfix.data.frame na.roughfix.default
Compute outlying measuresoutlier outlier.default outlier.randomForest
Partial dependence plotpartialPlot partialPlot.default partialPlot.randomForest
Plot method for randomForest objectsplot.randomForest
predict method for random forest objectspredict.randomForest
Classification and Regression with Random Forestprint.randomForest randomForest randomForest.default randomForest.formula
Random Forest Cross-Valdidation for feature selectionrfcv
Missing Value Imputations by randomForestrfImpute rfImpute.default rfImpute.formula
Show the NEWS filerfNews
Size of trees in an ensembletreesize
Tune randomForest for the optimal mtry parametertuneRF
Variable Importance PlotvarImpPlot
Variables used in a random forestvarUsed