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 Roxygen: list(markdown = TRUE) 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' Config/pak/sysreqs: cmake make Repository: https://mlr-org.r-universe.dev Date/Publication: 2026-03-16 13:01:03 UTC RemoteUrl: https://github.com/mlr-org/mlr3tuning RemoteRef: v1.6.0 RemoteSha: 0fccf22aaea32665dbf3191be815e1fe4c17287c Packaged: 2026-06-27 13:50:40 UTC; root Author: Marc Becker [cre, aut] (ORCID: ), Michel Lang [aut] (ORCID: ), Jakob Richter [aut] (ORCID: ), Bernd Bischl [aut] (ORCID: ), Daniel Schalk [aut] (ORCID: ) Maintainer: Marc Becker