Package: mlr3tuning 1.3.0

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.
Authors:
mlr3tuning_1.3.0.tar.gz
mlr3tuning_1.3.0.zip(r-4.5)mlr3tuning_1.3.0.zip(r-4.4)mlr3tuning_1.3.0.zip(r-4.3)
mlr3tuning_1.3.0.tgz(r-4.5-any)mlr3tuning_1.3.0.tgz(r-4.4-any)mlr3tuning_1.3.0.tgz(r-4.3-any)
mlr3tuning_1.3.0.tar.gz(r-4.5-noble)mlr3tuning_1.3.0.tar.gz(r-4.4-noble)
mlr3tuning_1.3.0.tgz(r-4.4-emscripten)mlr3tuning_1.3.0.tgz(r-4.3-emscripten)
mlr3tuning.pdf |mlr3tuning.html✨
mlr3tuning/json (API)
NEWS
# Install 'mlr3tuning' in R: |
install.packages('mlr3tuning', repos = c('https://mlr-org.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mlr-org/mlr3tuning/issues
Pkgdown site:https://mlr3tuning.mlr-org.com
bbotkhyperparameter-optimizationhyperparameter-tuningmachine-learningmlr3optimizationtunetuning
Last updated 3 months agofrom:466c2eb2a9 (on v1.3.0). Checks:8 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Feb 16 2025 |
R-4.5-win | OK | Feb 16 2025 |
R-4.5-mac | OK | Feb 16 2025 |
R-4.5-linux | OK | Feb 16 2025 |
R-4.4-win | OK | Feb 16 2025 |
R-4.4-mac | OK | Feb 16 2025 |
R-4.3-win | OK | Feb 16 2025 |
R-4.3-mac | OK | Feb 16 2025 |
Exports:ArchiveAsyncTuningArchiveAsyncTuningFrozenArchiveBatchTuningas_search_spaceas_tuneras_tunersassert_async_tuning_callbackassert_async_tuning_callbacksassert_batch_tuning_callbackassert_batch_tuning_callbacksassert_tunerassert_tuner_asyncassert_tuner_batchassert_tunersassert_tuning_instanceassert_tuning_instance_asyncassert_tuning_instance_batchauto_tunerAutoTunercallback_async_tuningcallback_batch_tuningCallbackAsyncTuningCallbackBatchTuningclbkclbksContextAsyncTuningContextBatchTuningextract_inner_tuning_archivesextract_inner_tuning_resultsmlr_callbacksmlr_terminatorsmlr_tunersObjectiveTuningObjectiveTuningAsyncObjectiveTuningBatchtiti_asynctnrtnrstrmtrmstunetune_nestedTunerTunerAsyncTunerAsyncDesignPointsTunerAsyncFromOptimizerAsyncTunerAsyncGridSearchTunerAsyncRandomSearchTunerBatchTunerBatchCmaesTunerBatchDesignPointsTunerBatchFromOptimizerBatchTunerBatchGenSATunerBatchGridSearchTunerBatchInternalTunerBatchIraceTunerBatchNLoptrTunerBatchRandomSearchTuningInstanceAsyncMultiCritTuningInstanceAsyncSingleCritTuningInstanceBatchMultiCritTuningInstanceBatchSingleCritTuningInstanceMultiCritTuningInstanceSingleCrit
Dependencies:backportsbbotkcheckmatecodetoolsdata.tabledigestevaluatefuturefuture.applyglobalslgrlistenvmlbenchmlr3mlr3measuresmlr3miscpalmerpenguinsparadoxparallellyPRROCR6uuid