mlr3tuning: Hyperparameter Optimization for 'mlr3' (original) (raw)

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: 1.2.0
Depends: mlr3 (≥ 0.20.0), paradox (≥ 1.0.1), R (≥ 3.1.0)
Imports: bbotk (≥ 1.3.0), checkmate (≥ 2.0.0), data.table, lgr, mlr3misc (≥ 0.15.1), R6
Suggests: adagio, future, GenSA, irace, knitr, mlflow, mlr3learners (≥ 0.7.0), mlr3pipelines (≥ 0.5.2), nloptr, rush, rmarkdown, rpart, testthat (≥ 3.0.0), xgboost
Published: 2024-11-08
DOI: 10.32614/CRAN.package.mlr3tuning
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
BugReports: https://github.com/mlr-org/mlr3tuning/issues
License: LGPL-3
URL: https://mlr3tuning.mlr-org.com,https://github.com/mlr-org/mlr3tuning
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mlr3tuning results

Documentation:

Downloads:

Reverse dependencies:

Reverse depends: MantaID, mlr3hyperband, mlr3mbo, mlr3tuningspaces
Reverse imports: DoubleML, mlr3verse, mlrintermbo, sense, SIAMCAT
Reverse suggests: miesmuschel, mlr3resampling, mlr3spatiotempcv, mlr3torch, mlr3viz

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=mlr3tuningto link to this page.