mlr3tuning: Hyperparameter Optimization for 'mlr3'

Hyperparameter optimization package of the mlr3 ecosystem. It features highly configurable search spaces via the paradox package and finds optimal hyperparameter configurations for any mlr3 learner. mlr3tuning works with several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in mlr3mbo) and Hyperband (in mlr3hyperband). Moreover, it can automatically optimize learners and estimate the performance of optimized models with nested resampling.

Version: 0.17.0
Depends: mlr3 (≥ 0.14.1), paradox (≥ 0.10.0), R (≥ 3.1.0)
Imports: bbotk (≥ 0.7.0), checkmate (≥ 2.0.0), data.table, lgr, mlr3misc (≥ 0.11.0), R6
Suggests: adagio, GenSA, irace, mlr3learners (≥ 0.5.5), mlr3pipelines, nloptr, rpart, testthat (≥ 3.0.0), xgboost
Published: 2022-11-18
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_0.17.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mlr3tuning_0.17.0.tgz, r-oldrel (arm64): mlr3tuning_0.17.0.tgz, r-release (x86_64): mlr3tuning_0.17.0.tgz, r-oldrel (x86_64): mlr3tuning_0.17.0.tgz
Old sources: mlr3tuning archive

Reverse dependencies:

Reverse depends: mlr3hyperband, mlr3mbo, mlr3tuningspaces
Reverse imports: DoubleML, MantaID, mlr3verse, mlrintermbo, sense, SIAMCAT
Reverse suggests: miesmuschel, mlr3spatiotempcv, mlr3viz


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