randomForest: Breiman and Cutler's Random Forests for Classification and Regression

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

Version: 4.6-12
Depends: R (≥ 2.5.0), stats
Suggests: RColorBrewer, MASS
Published: 2015-10-07
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: https://www.stat.berkeley.edu/~breiman/RandomForests/
NeedsCompilation: yes
Citation: randomForest citation info
Materials: NEWS
In views: Environmetrics, MachineLearning
CRAN checks: randomForest results

Downloads:

Reference manual: randomForest.pdf
Package source: randomForest_4.6-12.tar.gz
Windows binaries: r-devel: randomForest_4.6-12.zip, r-release: randomForest_4.6-12.zip, r-oldrel: randomForest_4.6-12.zip
OS X Mavericks binaries: r-release: randomForest_4.6-12.tgz, r-oldrel: randomForest_4.6-12.tgz
Old sources: randomForest archive

Reverse dependencies:

Reverse depends: AUCRF, bartMachine, BigTSP, D2C, interpretR, MAVTgsa, missForest, MixRF, mlDNA, ModelMap, partitionMap, quantregForest, RFgroove, rfPermute, roughrf, spikeslab, sprint, trimTrees, varSelRF
Reverse imports: abcrf, aCRM, aLFQ, bagRboostR, Biocomb, biomod2, CALIBERrfimpute, cem, CONDOP, conformal, CovSelHigh, ecospat, EnsembleBase, FSelector, fuzzyforest, gamclass, gencve, hybridEnsemble, imputeMissings, kernelFactory, LINselect, mlearning, NAM, nodeHarvest, nproc, optBiomarker, OTE, preprocomb, preproviz, pRF, randomForest.ddR, rasclass, RFmarkerDetector, rfUtilities, rminer, RTextTools, SPOT, SSDM, synthpop, TLBC, vita, VSURF
Reverse suggests: A3, BatchExperiments, BiodiversityR, boostr, Boruta, caret, caretEnsemble, ChemometricsWithR, COBRA, crtests, DAAG, DAAGxtras, Daim, discSurv, dismo, doMPI, dyn, e1071, emil, foreach, forestFloor, fscaret, GSIF, HSAUR, HSAUR2, HSAUR3, ICEbox, lulcc, mboost, mice, mlr, ModelGood, pander, pedometrics, pmml, purge, rattle, RStoolbox, subsemble, SuperLearner, TDMR, tmle.npvi, TunePareto, unbalanced, utiml, VHDClassification, visreg, wsrf, yaImpute