mlr3tuning: Tuning for 'mlr3'

Implements methods for hyperparameter tuning with 'mlr3', e.g. grid search, random search, generalized simulated annealing and iterated racing. Various termination criteria can be set and combined. The class 'AutoTuner' provides a convenient way to perform nested resampling in combination with 'mlr3'.

Version: 0.13.0
Depends: mlr3 (≥ 0.13.1), paradox (≥ 0.7.0), R (≥ 3.1.0)
Imports: bbotk (≥ 0.5.2), checkmate (≥ 2.0.0), data.table, lgr, mlr3misc (≥ 0.10.0), R6
Suggests: adagio, GenSA, irace, mlr3pipelines, nloptr, rpart, testthat (≥ 3.0.0)
Published: 2022-04-06
Author: Marc Becker ORCID iD [cre, aut], Michel Lang ORCID iD [aut], Jakob Richter ORCID iD [aut], Bernd Bischl ORCID iD [aut], Daniel Schalk ORCID iD [aut]
Maintainer: Marc Becker <marcbecker at>
License: LGPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mlr3tuning results


Reference manual: mlr3tuning.pdf


Package source: mlr3tuning_0.13.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mlr3tuning_0.12.1.tgz, r-release (x86_64): mlr3tuning_0.12.1.tgz, r-oldrel: mlr3tuning_0.12.1.tgz
Old sources: mlr3tuning archive

Reverse dependencies:

Reverse depends: mlr3hyperband, mlr3tuningspaces
Reverse imports: DoubleML, mlr3verse, mlrintermbo, sense
Reverse suggests: mlr3spatial, mlr3spatiotempcv, mlr3viz


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