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: 2.1-3.1
Depends: R (≥ 2.10)
Suggests: lattice
Published: 2023-05-05
Author: Friedrich Leisch and Evgenia Dimitriadou.
Maintainer: Friedrich Leisch <Friedrich.Leisch at>
License: GPL-2
NeedsCompilation: yes
Citation: mlbench citation info
Materials: README NEWS
CRAN checks: mlbench results


Reference manual: mlbench.pdf


Package source: mlbench_2.1-3.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mlbench_2.1-3.1.tgz, r-oldrel (arm64): mlbench_2.1-3.1.tgz, r-release (x86_64): mlbench_2.1-3.1.tgz, r-oldrel (x86_64): mlbench_2.1-3.1.tgz
Old sources: mlbench archive

Reverse dependencies:

Reverse depends: conformalClassification, GAMens
Reverse imports: bayesGAM, forestRK, FSinR, interactionRCS, MLInterfaces, mlr3, OddsPlotty, stream, TSDT
Reverse suggests: adabag, agghoo, alookr, archetypes, arf, arulesCBA, ATR, aum, bnclassify, bolasso, BoomSpikeSlab, BoostMLR, Boruta, caret, caretEnsemble, clusterSim, ConfusionTableR, Cubist,, dann, datarobot, discrim, doParallel, doSNOW, e1071, ecr, Elja, Evacluster, evtree, ExhaustiveSearch, EZtune, FCBF, flacco, flexmix, fscaret, FSelector, gamclass, GAparsimony, ggparty, GMDH2, h2o, hmclearn, HSAUR3, ipred, isotree, klaR, LLM, localICE, mboost, mlearning, mlexperiments, mllrnrs, mlr, mlr3cluster, mlr3pipelines, mlrCPO, mlt.docreg, neighbr, nestedcv, party, partykit, pdp, performanceEstimation, pre, r2pmml, randomForestSRC, rbooster, RBPcurve, RWeka, sjtable2df, skedastic, solitude, sparklyr, spikeSlabGAM, stabm, subsemble, SuperLearner, swag, tidypredict, tidyrules, tram, tramnet, treemisc, triplot, varrank, vip, vivo, zooimage


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