ranger: A Fast Implementation of Random Forests

A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Data from genome-wide association studies can be analyzed efficiently. In addition to data frames, datasets of class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') can be directly analyzed.

Version: 0.12.1
Depends: R (≥ 3.1)
Imports: Rcpp (≥ 0.11.2), Matrix
LinkingTo: Rcpp, RcppEigen
Suggests: survival, testthat
Published: 2020-01-10
Author: Marvin N. Wright [aut, cre], Stefan Wager [ctb], Philipp Probst [ctb]
Maintainer: Marvin N. Wright <cran at wrig.de>
BugReports: https://github.com/imbs-hl/ranger/issues
License: GPL-3
URL: https://github.com/imbs-hl/ranger
NeedsCompilation: yes
Citation: ranger citation info
Materials: NEWS
In views: MachineLearning, Survival
CRAN checks: ranger results

Downloads:

Reference manual: ranger.pdf
Package source: ranger_0.12.1.tar.gz
Windows binaries: r-devel: ranger_0.12.1.zip, r-release: ranger_0.12.1.zip, r-oldrel: ranger_0.12.1.zip
macOS binaries: r-release: ranger_0.12.1.tgz, r-oldrel: ranger_0.12.1.tgz
Old sources: ranger archive

Reverse dependencies:

Reverse depends: metaforest, RfEmpImp, tuneRanger
Reverse imports: abcrf, ADAPTS, alookr, AmpGram, AmyloGram, banter, BioMM, Boruta, causalweight, CornerstoneR, fairadapt, funest, genphen, healthcareai, hpiR, influential, memoria, miceRanger, missRanger, mlr3shiny, OOBCurve, orf, outForest, poolVIM, PrInCE, quantregRanger, radiant.model, randomForestExplainer, RCAS, REMP, rfinterval, riskRegression, rmweather, RNAmodR.ML, sambia, SCORPIUS, simPop, solitude, spm, SPOT, stablelearner, StratifiedMedicine, tbma, VIM, VSURF, worcs
Reverse suggests: arenar, batchtools, breakDown, butcher, cattonum, corrgrapher, DALEX, drifter, DriveML, dynwrap, ENMTools, fastshap, flashlight, forestControl, GSIF, HPLB, iBreakDown, iml, Infusion, IPMRF, knockoff, lime, lmtp, MachineShop, mlr, mlr3learners, mlrCPO, modelDown, modelplotr, modelStudio, nlpred, parsnip, pdp, piRF, purge, r2pmml, sperrorest, splitTools, SSLR, SuperLearner, superml, tidypredict, topdownr, tree.interpreter, triplot, varImp, vimp, vip

Linking:

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