Package: mlr3tuning
Title: Hyperparameter Optimization for 'mlr3'
Version: 1.6.0
Authors@R: c(
    person("Marc", "Becker", , "marcbecker@posteo.de", role = c("cre", "aut"),
           comment = c(ORCID = "0000-0002-8115-0400")),
    person("Michel", "Lang", , "michellang@gmail.com", role = "aut",
           comment = c(ORCID = "0000-0001-9754-0393")),
    person("Jakob", "Richter", , "jakob1richter@gmail.com", role = "aut",
           comment = c(ORCID = "0000-0003-4481-5554")),
    person("Bernd", "Bischl", , "bernd_bischl@gmx.net", role = "aut",
           comment = c(ORCID = "0000-0001-6002-6980")),
    person("Daniel", "Schalk", , "daniel.schalk@stat.uni-muenchen.de", role = "aut",
           comment = c(ORCID = "0000-0003-0950-1947"))
  )
Description: 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.
License: LGPL-3
URL: https://mlr3tuning.mlr-org.com,
        https://github.com/mlr-org/mlr3tuning
BugReports: https://github.com/mlr-org/mlr3tuning/issues
Depends: mlr3 (>= 0.23.0), paradox (>= 1.0.1), R (>= 3.3.0)
Imports: bbotk (>= 1.9.0), checkmate (>= 2.0.0), cli, data.table, lgr,
        mlr3misc (>= 0.15.1), R6
Suggests: adagio, future, GenSA, irace (>= 4.1.0), knitr, mirai,
        mlflow, mlr3learners (>= 0.14.0), mlr3pipelines (>= 0.5.2),
        nloptr, processx, redux, rush (>= 0.4.1), rmarkdown, rpart,
        testthat (>= 3.0.0), xgboost (>= 3.1.2.1)
VignetteBuilder: knitr
Config/testthat/edition: 3
Config/testthat/parallel: false
Encoding: UTF-8
NeedsCompilation: no
RoxygenNote: 7.3.3
Collate: 'ArchiveAsyncTuning.R' 'ArchiveAsyncTuningFrozen.R'
        'ArchiveBatchTuning.R' 'AutoTuner.R' 'CallbackAsyncTuning.R'
        'CallbackBatchTuning.R' 'ContextAsyncTuning.R'
        'ContextBatchTuning.R' 'ObjectiveTuning.R'
        'ObjectiveTuningAsync.R' 'ObjectiveTuningBatch.R'
        'mlr_tuners.R' 'Tuner.R' 'TunerAsync.R'
        'TunerAsyncDesignPoints.R' 'TunerAsyncFromOptimizerAsync.R'
        'TunerAsyncGridSearch.R' 'TunerAsyncRandomSearch.R'
        'TunerBatch.R' 'TunerBatchCmaes.R' 'TunerBatchDesignPoints.R'
        'TunerBatchFromBatchOptimizer.R' 'TunerBatchGenSA.R'
        'TunerBatchGridSearch.R' 'TunerBatchInternal.R'
        'TunerBatchIrace.R' 'TunerBatchNLoptr.R'
        'TunerBatchRandomSearch.R' 'TuningInstanceBatchSingleCrit.R'
        'TuningInstanceAsyncMulticrit.R'
        'TuningInstanceAsyncSingleCrit.R'
        'TuningInstanceBatchMulticrit.R' 'TuningInstanceMultiCrit.R'
        'TuningInstanceSingleCrit.R' 'as_search_space.R' 'as_tuner.R'
        'assertions.R' 'auto_tuner.R' 'bibentries.R'
        'extract_inner_tuning_archives.R'
        'extract_inner_tuning_results.R' 'helper.R' 'mlr_callbacks.R'
        'reexport.R' 'sugar.R' 'tune.R' 'tune_nested.R' 'zzz.R'
Packaged: 2026-03-16 13:03:43 UTC; marc
Author: Marc Becker [cre, aut] (ORCID: <https://orcid.org/0000-0002-8115-0400>),
  Michel Lang [aut] (ORCID: <https://orcid.org/0000-0001-9754-0393>),
  Jakob Richter [aut] (ORCID: <https://orcid.org/0000-0003-4481-5554>),
  Bernd Bischl [aut] (ORCID: <https://orcid.org/0000-0001-6002-6980>),
  Daniel Schalk [aut] (ORCID: <https://orcid.org/0000-0003-0950-1947>)
Maintainer: Marc Becker <marcbecker@posteo.de>
Repository: CRAN
Date/Publication: 2026-03-16 13:40:02 UTC
Built: R 4.4.3; ; 2026-04-11 02:58:37 UTC; windows
