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
Depends: R (≥ 2.10)
Suggests: lattice
Published: 2021-01-29
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.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: mlbench_2.1-3.tgz, r-oldrel: mlbench_2.1-3.tgz
Old sources: mlbench archive

Reverse dependencies:

Reverse depends: conformalClassification, GAMens, mpbart, trimTrees
Reverse imports: bayesGAM, forestRK, FSinR, MLInterfaces, mlr3, spFSR, stream, TSDT
Reverse suggests: adabag, alookr, archetypes, ATR, bnclassify, BoomSpikeSlab, BoostMLR, boostr, Boruta, caret, caretEnsemble, clusterSim, Cubist, dann, datarobot, discrim, doParallel, doSNOW, e1071, easyalluvial, evtree, ExhaustiveSearch, EZtune, FCBF, flacco, flexmix, fscaret, FSelector, gamclass, GAparsimony, ggparty, GMDH2, h2o, hmclearn, HSAUR3, IPMRF, ipred, klaR, LLM, localICE, mboost, mlearning, mlr, mlr3cluster, mlr3pipelines, mlrCPO, mlt.docreg, mobForest, neighbr, party, partykit, performanceEstimation, pre, r2pmml, randomForestSRC, RBPcurve, RODM, RWeka, skedastic, smartdata, sparklyr, spikeSlabGAM, SuperLearner, swag, tidypredict, tidyrules, tram, tramnet, triplot, varrank, vip, vivo, zooimage


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