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Changelog

Source: NEWS.md

mlr3tuning 1.4.0

CRAN release: 2025-06-04

  • feat: Resample stages from CallbackResample are now available in CallbackBatchTuning and CallbackAsyncTuning.
  • fix: The $predict_type was written to the model even when the AutoTuner was not trained.
  • feat: Internal tuned values are now visible in logs.
  • BREAKING CHANGE: Remove internal search space argument.
  • BREAKING CHANGE: The mlr3 ecosystem has a base logger now which is named mlr3. The mlr3/bbotk logger is a child of the mlr3 logger and is used for logging messages from the bbotk and mlr3tuning package.
  • feat: Classes are now printed with the cli package.

mlr3tuning 1.3.0

CRAN release: 2024-12-17

  • feat: Save ArchiveAsyncTuning to a data.table with ArchiveAsyncTuningFrozen.
  • perf: Save models on worker only when requested in ObjectiveTuningAsync.

mlr3tuning 1.2.1

CRAN release: 2024-11-26

  • refactor: Only pass extra to $assign_result().

mlr3tuning 1.2.0

CRAN release: 2024-11-08

  • feat: Add new callback clbk("mlr3tuning.one_se_rule") that selects the the hyperparameter configuration with the smallest feature set within one standard error of the best.
  • feat: Add new stages on_tuning_result_begin and on_result_begin to CallbackAsyncTuning and CallbackBatchTuning.
  • refactor: Rename stage on_result to on_result_end in CallbackAsyncTuning and CallbackBatchTuning.
  • docs: Extend the CallbackAsyncTuning and CallbackBatchTuning documentation.
  • compatibility: mlr3 0.22.0
  • compatibility: Work with new irace 4.0.0

mlr3tuning 1.1.0

CRAN release: 2024-10-27

  • fix: The as_data_table() functions do not unnest the x_domain colum anymore by default.
  • fix: to_tune(internal = TRUE) now also works if non-internal tuning parameters require have an .extra_trafo.
  • feat: It is now possible to pass an internal_search_space manually. This allows to use parameter transformations on the primary search space in combination with internal hyperparameter tuning.
  • refactor: The Tuner pass extra information of the result in the extra parameter now.

mlr3tuning 1.0.2

CRAN release: 2024-10-14

  • refactor: Extract internal tuned values in instance.

mlr3tuning 1.0.1

CRAN release: 2024-09-10

  • refactor: Replace internal tuning callback.
  • perf: Delete intermediate BenchmarkResult in ObjectiveTuningBatch after optimization.

mlr3tuning 1.0.0

CRAN release: 2024-06-29

  • feat: Introduce asynchronous optimization with the TunerAsync and TuningInstanceAsync* classes.
  • BREAKING CHANGE: The Tuner class is TunerBatch now.
  • BREAKING CHANGE: THe TuningInstanceSingleCrit and TuningInstanceMultiCrit classes are TuningInstanceBatchSingleCrit and TuningInstanceBatchMultiCrit now.
  • BREAKING CHANGE: The CallbackTuning class is CallbackBatchTuning now.
  • BREAKING CHANGE: The ContextEval class is ContextBatchTuning now.
  • refactor: Remove hotstarting from batch optimization due to low performance.
  • refactor: The option evaluate_default is a callback now.

mlr3tuning 0.20.0

CRAN release: 2024-03-05

  • compatibility: Work with new paradox version 1.0.0
  • fix: TunerIrace failed with logical parameters and dependencies.
  • Added marshaling support to AutoTuner

mlr3tuning 0.19.2

CRAN release: 2023-11-28

  • refactor: Change thread limits.

mlr3tuning 0.19.1

CRAN release: 2023-11-20

  • refactor: Speed up the tuning process by minimizing the number of deep clones and parameter checks.
  • fix: Set store_benchmark_result = TRUE if store_models = TRUE when creating a tuning instance.
  • fix: Passing a terminator in tune_nested() did not work.

mlr3tuning 0.19.0

CRAN release: 2023-06-26

  • fix: Add $phash() method to AutoTuner.
  • fix: Include Tuner in hash of AutoTuner.
  • feat: Add new callback that scores the configurations on additional measures while tuning.
  • feat: Add vignette about adding new tuners which was previously part of the mlr3book.

mlr3tuning 0.18.0

CRAN release: 2023-03-08

  • BREAKING CHANGE: The method parameter of tune(), tune_nested() and auto_tuner() is renamed to tuner. Only Tuner objects are accepted now. Arguments to the tuner cannot be passed with ... anymore.
  • BREAKING CHANGE: The tuner parameter of AutoTuner is moved to the first position to achieve consistency with the other functions.
  • docs: Update resources sections.
  • docs: Add list of default measures.
  • fix: Add allow_hotstarting, keep_hotstart_stack and keep_models flags to AutoTuner and auto_tuner().

mlr3tuning 0.17.2

CRAN release: 2022-12-22

  • feat: AutoTuner accepts instantiated resamplings now. The AutoTuner checks if all row ids of the inner resampling are present in the outer resampling train set when nested resampling is performed.
  • fix: Standalone Tuner did not create a ContextOptimization.

mlr3tuning 0.17.1

CRAN release: 2022-12-07

  • fix: The ti() function did not accept callbacks.

mlr3tuning 0.17.0

CRAN release: 2022-11-18

  • feat: The methods $importance(), $selected_features(), $oob_error() and $loglik() are forwarded from the final model to the AutoTuner now.
  • refactor: The AutoTuner stores the instance and benchmark result if store_models = TRUE.
  • refactor: The AutoTuner stores the instance if store_benchmark_result = TRUE.

mlr3tuning 0.16.0

CRAN release: 2022-11-08

  • feat: Add new callback that enables early stopping while tuning to mlr_callbacks.
  • feat: Add new callback that backups the benchmark result to disk after each batch.
  • feat: Create custom callbacks with the callback_batch_tuning() function.

mlr3tuning 0.15.0

CRAN release: 2022-10-21

  • fix: AutoTuner did not accept TuningSpace objects as search spaces.
  • feat: Add ti() function to create a TuningInstanceSingleCrit or TuningInstanceMultiCrit.
  • docs: Documentation has a technical details section now.
  • feat: New option for extract_inner_tuning_results() to return the tuning instances.

mlr3tuning 0.14.0

CRAN release: 2022-08-25

  • feat: Add option evaluate_default to evaluate learners with hyperparameters set to their default values.
  • refactor: From now on, the default of smooth is FALSE for TunerGenSA.

mlr3tuning 0.13.1

CRAN release: 2022-05-03

  • feat: Tuner objects have the field $id now.

mlr3tuning 0.13.0

CRAN release: 2022-04-06

  • feat: Allow to pass Tuner objects as method in tune() and auto_tuner().
  • docs: Link Tuner to help page of bbotk::Optimizer.
  • feat: Tuner objects have the optional field $label now.
  • feat: as.data.table() functions for objects of class Dictionary have been extended with additional columns.

mlr3tuning 0.12.1

CRAN release: 2022-02-25

  • feat: Add a as.data.table.DictionaryTuner function.
  • feat: New $help() method which opens the manual page of a Tuner.

mlr3tuning 0.12.0

CRAN release: 2022-02-17

  • feat: as_search_space() function to create search spaces from Learner and ParamSet objects. Allow to pass TuningSpace objects as search_space in TuningInstanceSingleCrit and TuningInstanceMultiCrit.
  • feat: The mlr3::HotstartStack can now be removed after tuning with the keep_hotstart_stack flag.
  • feat: The Archive stores errors and warnings of the learners.
  • feat: When no measure is provided, the default measure is used in auto_tuner() and tune_nested().

mlr3tuning 0.11.0

CRAN release: 2022-02-02

  • fix: $assign_result() method in TuningInstanceSingleCrit when search space is empty.
  • feat: Default measure is used when no measure is supplied to TuningInstanceSingleCrit.

mlr3tuning 0.10.0

CRAN release: 2022-01-20

  • Fixes bug in TuningInstanceMultiCrit$assign_result().
  • Hotstarting of learners with previously fitted models.
  • Remove deep clones to speed up tuning.
  • Add store_models flag to auto_tuner().
  • Add "noisy" property to ObjectiveTuning.

mlr3tuning 0.9.0

CRAN release: 2021-09-14

  • Adds AutoTuner$base_learner() method to extract the base learner from nested learner objects.
  • tune() supports multi-criteria tuning.
  • Allows empty search space.
  • Adds TunerIrace from irace package.
  • extract_inner_tuning_archives() helper function to extract inner tuning archives.
  • Removes ArchiveTuning$extended_archive() method. The mlr3::ResampleResults are joined automatically by as.data.table.TuningArchive() and extract_inner_tuning_archives().

mlr3tuning 0.8.0

CRAN release: 2021-03-12

  • Adds tune(), auto_tuner() and tune_nested() sugar functions.
  • TuningInstanceSingleCrit, TuningInstanceMultiCrit and AutoTuner can be initialized with store_benchmark_result = FALSE and store_models = TRUE to allow measures to access the models.
  • Prettier printing methods.

mlr3tuning 0.7.0

CRAN release: 2021-02-11

  • Fix TuningInstance*$assign_result() errors with required parameter bug.
  • Shortcuts to access $learner(), $learners(), $learner_param_vals(), $predictions() and $resample_result() from benchmark result in archive.
  • extract_inner_tuning_results() helper function to extract inner tuning results.

mlr3tuning 0.6.0

CRAN release: 2021-01-24

  • ArchiveTuning$data is a public field now.

mlr3tuning 0.5.0

CRAN release: 2020-12-07

  • Adds TunerCmaes from adagio package.
  • Fix predict_type in AutoTuner.
  • Support to set TuneToken in Learner$param_set and create a search space from it.
  • The order of the parameters in TuningInstanceSingleCrit and TuningInstanceSingleCrit changed.

mlr3tuning 0.4.0

CRAN release: 2020-10-07

  • Option to control store_benchmark_result, store_models and check_values in AutoTuner. store_tuning_instance must be set as a parameter during initialization.
  • Fixes check_values flag in TuningInstanceSingleCrit and TuningInstanceMultiCrit.
  • Removed dependency on orphaned package bibtex.

mlr3tuning 0.3.0

CRAN release: 2020-09-08

  • Compact in-memory representation of R6 objects to save space when saving mlr3 objects via saveRDS(), serialize() etc.
  • Archive is ArchiveTuning now which stores the benchmark result in $benchmark_result. This change removed the resample results from the archive but they can be still accessed via the benchmark result.
  • Warning message if external package for tuning is not installed.
  • To retrieve the inner tuning results in nested resampling, as.data.table(rr)$learner[[1]]$tuning_result must be used now.

mlr3tuning 0.2.0

CRAN release: 2020-07-28

  • TuningInstance is now TuningInstanceSingleCrit. TuningInstanceMultiCrit is still available for multi-criteria tuning.
  • Terminators are now accessible by trm() and trms() instead of term() and terms().
  • Storing of resample results is optional now by using the store_resample_result flag in TuningInstanceSingleCrit and TuningInstanceMultiCrit
  • TunerNLoptr adds non-linear optimization from the nloptr package.
  • Logging is controlled by the bbotk logger now.
  • Proposed points and performance values can be checked for validity by activating the check_values flag in TuningInstanceSingleCrit and TuningInstanceMultiCrit.

mlr3tuning 0.1.3

  • mlr3tuning now depends on the bbotk package for basic tuning objects. Terminator classes now live in bbotk. As a consequence ObjectiveTuning inherits from bbotk::Objective, TuningInstance from bbotk::OptimInstance and Tuner from bbotk::Optimizer
  • TuningInstance$param_set becomes TuningInstance$search_space to avoid confusion as the param_set usually contains the parameters that change the behavior of an object.
  • Tuning is triggered by $optimize() instead of $tune()

mlr3tuning 0.1.2

CRAN release: 2020-01-31

  • Fixed a bug in AutoTuner where a $clone() was missing. Tuning results are unaffected, only stored models contained wrong hyperparameter values (#223).
  • Improved output log (#218).

mlr3tuning 0.1.1

CRAN release: 2019-12-06

  • Maintenance release.

mlr3tuning 0.1.0

CRAN release: 2019-09-30

  • Initial prototype.