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]

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randomForest/json (API)
NEWS

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

Peer review:

Datasets:

On CRAN:

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

12.25 score 45 stars 275 packages 34k scripts 141k downloads 1.4k mentions 18 exports 0 dependencies

Last updated 2 months agofrom:0ad64d71e8. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-win-x86_64OKNov 21 2024
R-4.5-linux-x86_64OKNov 21 2024
R-4.4-win-x86_64OKNov 21 2024
R-4.4-mac-x86_64OKNov 21 2024
R-4.4-mac-aarch64OKNov 21 2024
R-4.3-win-x86_64OKNov 21 2024
R-4.3-mac-x86_64OKNov 21 2024
R-4.3-mac-aarch64OKNov 21 2024

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