Classification and regression based on a forest of trees using random inputs.
Version: | 4.6-10 |
Depends: | R (≥ 2.5.0), stats |
Suggests: | RColorBrewer, MASS |
Published: | 2014-07-17 |
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_4.6-10.tar.gz |
Windows binaries: | r-devel: randomForest_4.6-10.zip, r-release: randomForest_4.6-10.zip, r-oldrel: randomForest_4.6-10.zip |
OS X Snow Leopard binaries: | r-release: randomForest_4.6-10.tgz, r-oldrel: randomForest_4.6-10.tgz |
OS X Mavericks binaries: | r-release: randomForest_4.6-10.tgz |
Old sources: | randomForest archive |
Reverse depends: | AUCRF, bartMachine, BigTSP, Boruta, cem, conformal, D2C, interpretR, MAVTgsa, missForest, mlDNA, ModelMap, partitionMap, quantregForest, rfUtilities, roughrf, spikeslab, sprint, trimTrees, varSelRF, VSURF |
Reverse imports: | aCRM, aLFQ, bagRboostR, biomod2, CALIBERrfimpute, ecospat, EnsembleBase, FSelector, gamclass, hybridEnsemble, kernelFactory, mice, mlearning, nodeHarvest, optBiomarker, rasclass, RFmarkerDetector, rfPermute, rminer, RTextTools |
Reverse suggests: | A3, BatchExperiments, BiodiversityR, boostr, caret, caretEnsemble, ChemometricsWithR, COBRA, DAAG, DAAGxtras, Daim, dismo, doMPI, dyn, e1071, emil, foreach, fscaret, GSIF, HSAUR, HSAUR2, HSAUR3, ICEbox, LINselect, mboost, mlr, ModelGood, pmml, rattle, SPOT, subsemble, SuperLearner, TDMR, tmle.npvi, TunePareto, VHDClassification, wsrf, yaImpute |