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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:0.17.0
Depends:R (≥ 3.1)
Imports:Rcpp (≥ 0.11.2),Matrix
LinkingTo:Rcpp,RcppEigen
Suggests:survival,testthat
Published:2024-11-08
DOI:10.32614/CRAN.package.ranger
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://imbs-hl.github.io/ranger/,https://github.com/imbs-hl/ranger
NeedsCompilation:yes
Citation:ranger citation info
Materials:NEWS
In views:MachineLearning,Survival
CRAN checks:ranger results

Documentation:

Reference manual:ranger.html ,ranger.pdf

Downloads:

Package source: ranger_0.17.0.tar.gz
Windows binaries: r-devel:ranger_0.17.0.zip, r-release:ranger_0.17.0.zip, r-oldrel:ranger_0.17.0.zip
macOS binaries: r-release (arm64):ranger_0.17.0.tgz, r-oldrel (arm64):ranger_0.17.0.tgz, r-release (x86_64):ranger_0.17.0.tgz, r-oldrel (x86_64):ranger_0.17.0.tgz
Old sources: ranger archive

Reverse dependencies:

Reverse depends:causalweight,ClassificationEnsembles,Iscores,LogisticEnsembles,multimedia,OptHoldoutSize,PKLMtest,RfEmpImp,SPARRAfairness,tuneRanger
Reverse imports:ADAPTS,alookr,AmpGram,AmyloGram,AnimalSequences,arf,AWAggregator,Boruta,C443,CancerGram,CaseBasedReasoning,CCI,ClassifyR,collinear,comets,CompositionalML,CoxAIPW,crossurr,ddecompose,ddml,discSurv,drpop,e2tree,EFAfactors,enmSdmX,fairadapt,flevr,fuzzylink,gapclosing,geomod,GRSxE,handwriterRF,hedgedrf,hpiR,hypoRF,influential,Infusion,ipd,IVDML,ldmppr,memoria,metaforest,meteo,miceRanger,missForest,missForestPredict,missRanger,mistyR,MLDataR,MLFS,mlmts,MRTAnalysis,MSiP,multiclassPairs,MUVR2,ocf,OOBCurve,optRF,orf,outForest,phenomis,PND.heter.cluster,poolVIM,PrInCE,quantregRanger,randomForestExplainer,RaSEn,RCAS,REMP,rfinterval,RFlocalfdr,rfVarImpOOB,rfvimptest,riskRegression,rjaf,rmweather,RNAmodR.ML,RobustPrediction,roseRF,RPIV,sambia,scDiagnostics,scHiCcompare,SCORPIUS,SEMdeep,seqimpute,shadowVIMP,simPop,SISIR,SLOS,solitude,spatialRF,spFSR,spm,stablelearner,Statial,StratifiedMedicine,subscreen,synthpop,tall,TangledFeatures,text2emotion,text2sdg,tramicp,TSCI,tsensembler,ubair,utsf,vaccine,VIM,VIMPS,viraldomain,viralmodels,worcs
Reverse suggests:arenar,autostats,batchtools,biotmle,bnns,breakDown,butcher,CALIBERrfimpute,CausalGPS,cdgd,CimpleG,confcons,cpi,DALEX,DALEXtra,decoupleR,DeepLearningCausal,DirectEffects,dlookr,DoubleML,drifter,dynwrap,ENMTools,explainer,FactorHet,fairmodels,familiar,fastml,fastshap,filtro,finetune,fmeffects,forestControl,fuseMLR,GenericML,HPLB,iBreakDown,iml,important,ingredients,innsight,knockoff,lime,lmtp,MachineShop,MantaID,mcboost,micd,mice,miesmuschel,mllrnrs,mlr,mlr3fairness,mlr3learners,mlr3mbo,mlr3pipelines,mlr3shiny,mlr3spatial,mlr3summary,mlr3superlearner,mlr3tuningspaces,mlr3viz,mlrCPO,mlrintermbo,mlsurvlrnrs,MLwrap,modelDown,modelStudio,MSclassifR,multiDEGGs,nestedcv,nlpred,parsnip,pathMED,pdp,PieGlyph,pminternal,polle,PortfolioTesteR,postcard,purge,qeML,RobinCar,SAiVE,SDModels,sense,sirus,soilassessment,sperrorest,spmodel,stacks,SuperLearner,survex,targeted,tdarec,text,tidyAML,tidypredict,tidysdm,tidysynthesis,topdownr,tram,transportr,tree.interpreter,txshift,varImp,vetiver,vimp,vivid,VSURF
Reverse enhances:vip

Linking:

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