Package: mlr3tuning 1.2.0
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_1.2.0.tar.gz
mlr3tuning_1.2.0.zip(r-4.5)mlr3tuning_1.2.0.zip(r-4.4)mlr3tuning_1.2.0.zip(r-4.3)
mlr3tuning_1.2.0.tgz(r-4.4-any)mlr3tuning_1.2.0.tgz(r-4.3-any)
mlr3tuning_1.2.0.tar.gz(r-4.5-noble)mlr3tuning_1.2.0.tar.gz(r-4.4-noble)
mlr3tuning_1.2.0.tgz(r-4.4-emscripten)mlr3tuning_1.2.0.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
bbotkhyperparameter-optimizationhyperparameter-tuningmachine-learningmlr3optimizationtunetuning
Last updated 16 days agofrom:a204a90045 (on v1.2.0). Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 08 2024 |
R-4.5-win | OK | Nov 08 2024 |
R-4.5-linux | OK | Nov 08 2024 |
R-4.4-win | OK | Nov 08 2024 |
R-4.4-mac | OK | Nov 08 2024 |
R-4.3-win | OK | Nov 08 2024 |
R-4.3-mac | OK | Nov 08 2024 |
Exports:ArchiveAsyncTuningArchiveBatchTuningas_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