mlr3tuning 0.13.0
CRAN release: 2022-04-06
- feat: Allow to pass
Tuner
objects asmethod
intune()
andauto_tuner()
. - docs: Link
Tuner
to help page ofbbotk::Optimizer
. - feat:
Tuner
objects have the optional field$label
now. - feat:
as.data.table()
functions for objects of classDictionary
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 aTuner
.
mlr3tuning 0.12.0
CRAN release: 2022-02-17
- feat:
as_search_space()
function to create search spaces fromLearner
andParamSet
objects. Allow to passTuningSpace
objects assearch_space
inTuningInstanceSingleCrit
andTuningInstanceMultiCrit
. - feat: The
mlr3::HotstartStack
can now be removed after tuning with thekeep_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()
andtune_nested()
.
mlr3tuning 0.11.0
CRAN release: 2022-02-02
- fix:
$assign_result()
method inTuningInstanceSingleCrit
when search space is empty. - feat: Default measure is used when no measure is supplied to
TuningInstanceSingleCrit
.
mlr3tuning 0.10.0
CRAN release: 2022-01-20
- Fixes bug in
TuningInstanceMultiCrit$assign_result()
. - Hotstarting of learners with previously fitted models.
- Remove deep clones to speed up tuning.
- Add
store_models
flag toauto_tuner()
. - Add
"noisy"
property toObjectiveTuning
.
mlr3tuning 0.9.0
CRAN release: 2021-09-14
- Adds
AutoTuner$base_learner()
method to extract the base learner from nested learner objects. -
tune()
supports multi-criteria tuning. - Allows empty search space.
- Adds
TunerIrace
fromirace
package. -
extract_inner_tuning_archives()
helper function to extract inner tuning archives. - Removes
ArchiveTuning$extended_archive()
method. Themlr3::ResampleResults
are joined automatically byas.data.table.TuningArchive()
andextract_inner_tuning_archives()
.
mlr3tuning 0.8.0
CRAN release: 2021-03-12
- Adds
tune()
,auto_tuner()
andtune_nested()
sugar functions. -
TuningInstanceSingleCrit
,TuningInstanceMultiCrit
andAutoTuner
can be initialized withstore_benchmark_result = FALSE
andstore_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$resample_result()
from benchmark result in archive. -
extract_inner_tuning_results()
helper function to extract inner tuning results.
mlr3tuning 0.5.0
CRAN release: 2020-12-07
- Adds
TunerCmaes
fromadagio
package. - Fix
predict_type
inAutoTuner
. - Support to set
TuneToken
inLearner$param_set
and create a search space from it. - The order of the parameters in
TuningInstanceSingleCrit
andTuningInstanceSingleCrit
changed.
mlr3tuning 0.4.0
CRAN release: 2020-10-07
- Option to control
store_benchmark_result
,store_models
andcheck_values
inAutoTuner
.store_tuning_instance
must be set as a parameter during initialization. - Fixes
check_values
flag inTuningInstanceSingleCrit
andTuningInstanceMultiCrit
. - 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
isArchiveTuning
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]]$tuning_result
must be used now.
mlr3tuning 0.2.0
CRAN release: 2020-07-28
-
TuningInstance
is nowTuningInstanceSingleCrit
.TuningInstanceMultiCrit
is still available for multi-criteria tuning. - Terminators are now accessible by
trm()
andtrms()
instead ofterm()
andterms()
. - Storing of resample results is optional now by using the
store_resample_result
flag inTuningInstanceSingleCrit
andTuningInstanceMultiCrit
-
TunerNLoptr
adds non-linear optimization from the nloptr package. - Logging is controlled by the
bbotk
logger now. - Proposed points and performance values can be checked for validity by activating the
check_values
flag inTuningInstanceSingleCrit
andTuningInstanceMultiCrit
.
mlr3tuning 0.1.3
- mlr3tuning now depends on the
bbotk
package for basic tuning objects.Terminator
classes now live inbbotk
. As a consequenceObjectiveTuning
inherits frombbotk::Objective
,TuningInstance
frombbotk::OptimInstance
andTuner
frombbotk::Optimizer
-
TuningInstance$param_set
becomesTuningInstance$search_space
to avoid confusion as theparam_set
usually contains the parameters that change the behavior of an object. - Tuning is triggered by
$optimize()
instead of$tune()