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mlbench: Machine Learning Benchmark Problems

A collection of artificial and real-world machine learning benchmark problems, including, e.g., several data sets from the UCI repository.

Version:2.1-6
Depends:R (≥ 2.10)
Suggests:lattice
Published:2024-12-30
DOI:10.32614/CRAN.package.mlbench
Author:Friedrich LeischORCID iD [aut] (maintainer up to 2024), Evgenia Dimitriadou [aut], Kurt HornikORCID iD [cre]
Maintainer:Kurt Hornik <Kurt.Hornik at R-project.org>
License:GPL-2
NeedsCompilation:yes
Citation:mlbench citation info
Materials:README,NEWS
CRAN checks:mlbench results

Documentation:

Reference manual:mlbench.html ,mlbench.pdf

Downloads:

Package source: mlbench_2.1-6.tar.gz
Windows binaries: r-devel:mlbench_2.1-6.zip, r-release:mlbench_2.1-6.zip, r-oldrel:mlbench_2.1-6.zip
macOS binaries: r-release (arm64):mlbench_2.1-6.tgz, r-oldrel (arm64):mlbench_2.1-6.tgz, r-release (x86_64):mlbench_2.1-6.tgz, r-oldrel (x86_64):mlbench_2.1-6.tgz
Old sources: mlbench archive

Reverse dependencies:

Reverse depends:conformalClassification,GAMens
Reverse imports:CIpostSelect,clusterWebApp,forestRK,MLInterfaces,mlr3,OddsPlotty,stream,TSDT
Reverse suggests:adabag,agghoo,alookr,archetypes,arf,arulesCBA,ATR,aum,BKP,bnclassify,bnns,bolasso,BoomSpikeSlab,BoostMLR,Boruta,caret,caretEnsemble,clusterSim,ConfusionTableR,Cubist,cuda.ml,dann,datarobot,discrim,doParallel,doSNOW,e1071,easyalluvial,ecr,Elja,Evacluster,evtree,ExhaustiveSearch,explainer,EZtune,fastml,flacco,flexmix,FSelector,gamclass,GAparsimony,ggparty,GMDH2,gtregression,h2o,hmclearn,HSAUR3,interactionRCS,IPMRF,ipred,isotree,klaR,LLM,localICE,mboost,mlearning,mlexperiments,mllrnrs,mlr,mlr3cluster,mlr3pipelines,mlrCPO,mlt.docreg,neighbr,nestedcv,party,partykit,pdp,pre,r2pmml,randomForestSRC,rbooster,RBPcurve,roclab,RWeka,sjtable2df,skedastic,solitude,sparklyr,spikeSlabGAM,stabm,stressor,subsemble,SuperLearner,swag,T4transport,tidydann,tidypredict,tidyrules,tram,tramnet,trtf,varPro,vcrpart,vip,vivo,zooimage

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=mlbenchto link to this page.

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