randomForest: Breiman and Cutler's random forests for classification and regression

Classification and regression based on a forest of trees using random inputs.

Version: 4.6-7
Depends: R (≥ 2.5.0), stats
Suggests: RColorBrewer, MASS
Published: 2012-10-16
Author: Fortran original by Leo Breiman and Adele Cutler, R port by Andy Liaw and Matthew Wiener.
Maintainer: Andy Liaw <andy_liaw at merck.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://stat-www.berkeley.edu/users/breiman/RandomForests
NeedsCompilation: yes
Citation: randomForest citation info
Materials: NEWS
In views: Environmetrics, MachineLearning
CRAN checks: randomForest results


Reference manual: randomForest.pdf
Package source: randomForest_4.6-7.tar.gz
MacOS X binary: randomForest_4.6-7.tgz
Windows binary: randomForest_4.6-7.zip
Old sources: randomForest archive

Reverse dependencies:

Reverse depends: AUCRF, bartMachine, BigTSP, Boruta, cem, KsPlot, missForest, mlDNA, ModelMap, MVpower, partitionMap, quantregForest, rfPermute, spikeslab, varSelRF, VSURF
Reverse imports: aCRM, bagRboostR, biomod2, bootfs, CALIBERrfimpute, FSelector, gamclass, GSIF, hybridEnsemble, kernelFactory, mice, mlearning, nodeHarvest, optBiomarker, rasclass, RTextTools
Reverse suggests: A3, aLFQ, BatchExperiments, BiodiversityR, caret, ChemometricsWithR, classifly, COBRA, DAAG, DAAGxtras, Daim, dismo, doMPI, dyn, e1071, foreach, fscaret, HSAUR, HSAUR2, ICEbox, LINselect, mlr, modelcf, ModelGood, opm, pmml, rattle, rminer, SPOT, SuperLearner, TDMR, tmle.npvi, TunePareto, VHDClassification, wsrf, yaImpute