Due to the high amount of packages in the mlr3 ecosystem, it is hard to keep up with the latest changes across all packages. This posts gives an overview by listing the recent release notes of mlr3 packages from the last quarter. Note that only CRAN packages are listed here and the sort order is alphabetically.
mlr3cluster 0.1.6
Description Cluster Extension for ‘mlr3’
- Add states as row names to
usarrest
task. - Remove dictionary items after unloading package.
mlr3cluster 0.1.5
- Added Mclust learner
- Fix error associated with new dbscan release
mlr3tuning 0.17.2
Description Hyperparameter Optimization for ‘mlr3’
- feat:
AutoTuner
accepts instantiated resamplings now. TheAutoTuner
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 aContextOptimization
.
mlr3tuning 0.17.1
- fix: The
ti()
function did not accept callbacks.
mlr3tuning 0.17.0
- feat: The methods
$importance()
,$selected_features()
,$oob_error()
and$loglik()
are forwarded from the final model to theAutoTuner
now. - refactor: The
AutoTuner
stores the instance and benchmark result ifstore_models = TRUE
. - refactor: The
AutoTuner
stores the instance ifstore_benchmark_result = TRUE
.
mlr3tuning 0.16.0
- 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_tuning()
function.
mlr3tuning 0.15.0
- fix:
AutoTuner
did not acceptTuningSpace
objects as search spaces. - feat: Add
ti()
function to create aTuningInstanceSingleCrit
orTuningInstanceMultiCrit
. - docs: Documentation has a technical details section now.
- feat: New option for
extract_inner_tuning_results()
to return the tuning instances.
mlr3fselect 0.9.0
Description Feature Selection for ‘mlr3’
- fix: Add
genalg
to required packages ofFSelectorGeneticSearch
. - feat: Add new callback that backups the benchmark result to disk after each batch.
- feat: Create custom callbacks with the
callback_fselect()
function.
mlr3fselect 0.8.0
- refactor:
FSelectorRFE
throws an error if the learner does not support the$importance()
method. - refactor: The
AutoFSelector
stores the instance and benchmark result ifstore_models = TRUE
. - refactor: The
AutoFSelector
stores the instance ifstore_benchmark_result = TRUE
. - feat: Add missing parameters from
AutoFSelector
toauto_fselect()
. - feat: Add
fsi()
function to create aFSelectInstanceSingleCrit
orFSelectInstanceMultiCrit
. - refactor: Remove
unnest
option fromas.data.table.ArchiveFSelect()
function.
mlr3mbo 0.1.1
Description Flexible Bayesian Optimization
- Initial CRAN upload
mlr3spatial 0.3.1
Description Support for Spatial Objects Within the ‘mlr3’ Ecosystem
- chore: Remove
rgdal
dependency and requireraster
version 3.6-11.
mlr3spatial 0.3.0
- feat: Add prediction on vector data to
spatial_predict()
.
mlr3oml 0.7.0
Description Connector Between ‘mlr3’ and ‘OpenML’
- feature: Add argument
task_type
to functionlist_oml_tasks()
. - fix: strings and nominals are distinguished for parquet files
- docs: Fixed some OpenML links
- docs: Renamed the docs for OpenML objects
- Renamed the sugar functions from:
oml_data()
is nowodt()
oml_task()
is nowotsk()
oml_flow()
is nowoflw()
oml_run()
is noworn
oml_collection()
is nowocl()
- Addresses a CRAN issue: examples fail gracefully if OpenML server is busy.
bbotk 0.7.2
Description Black-Box Optimization Toolkit
- fix: Standalone
Tuner
andFSelector
were rejected byContextOptimization
.
bbotk 0.7.1
- feat: Data unrelated to a specific point evaluation can be written to
Archive$data_extra
.
bbotk 0.7.0
- fix:
Terminator$format(with_params = TRUE)
printed an empty list when no parameter was set. - refactor:
OptimizerIrace
automatically added theinstances
parameter toObjective$constants
. From now on, theinstances
parameter can be also set manually. - BREAKING CHANGE:
branin(xs)
is nowbranin(x1, x2, noise)
andbranin_wu(x1, x2, fidelity)
. - feat: Add
ObjectiveRFunMany
that can evaluate a list of configurations with a user supplied function. - fix: If all configurations were missing a parameter,
ObjectiveRFunDt$eval_many()
did not create a column withNA
for the missing parameter. - refactor: The default of
digits
inOptimizerIrace
is 15 now to avoid rounding errors. - refactor: The bounds of double parameters were processed with only 4 decimal places in
OptimizerIrace
. By default, the bounds of double parameters are represented with 15 decimal places now. Thedigits
parameter ofOptimizerIrace
also changes number of decimal places of the bounds now.
bbotk 0.6.0
- fix:
OptimizerIrace
did not work with parameters with multiple dependencies. - feat: Add new callback that backups the archive to disk to
mlr_callbacks
. - feat: Create custom callbacks with the
callback_optimization()
function.
mlr3tuningspaces 0.3.3
Description Search Spaces for ‘mlr3’
- fix: Extra
paradox::TuneToken
inlts()
were not passed to learners created with$get_learner()
. - docs: Add
lts()
return.
mlr3tuningspaces 0.3.2
- docs: Add
mlr_tuning_spaces
prefix to aliases.
mlr3tuningspaces 0.3.1
- docs: Add glmnet description.
mlr3hyperband 0.4.4
Description Hyperband for ‘mlr3’
- fix: Remove
emoa
from required packages ofOptimizerSuccessiveHalving
.
mlr3hyperband 0.4.3
- docs: Examples use
branin_wu()
function now.
mlr3spatiotempcv 2.0.3
Description Spatiotemporal Resampling Methods for ‘mlr3’
- add
label
support for built-in tasks - adhere to CRAN “noSuggests” policy
mlr3verse 0.2.7
Description Easily Install and Load the ‘mlr3’ Package Family
- Updated reexports.
mlr3verse 0.2.6
- Updated reexports.
mlr3 0.14.1
Description Machine Learning in R - Next Generation
- Removed depdency on package
distr6
. - Fixed reassembling of
GraphLearner
. - Fixed bug where the measured elapsed time was 0: https://stackoverflow.com/questions/73797845/mlr3-benchmarking-with-elapsed-time-measure
- Fixed
as_prediction_classif()
fordata.frame()
input (#872). - Improved the error message when predict type of fallback learner does not match the predict type of the learner (mlr-org/mlr3extralearners#241).
- The test set is now available to the
Learner
during train for early stopping.
mlr3benchmark 0.1.4
Description Analysis and Visualisation of Benchmark Experiments
- Add
friedman_global
argument to posthoc tests and to autoplots to allow methods and plots to run even if the global Friedman test fails (i.e. don’t reject null) - New maintainer: Sebastian Fischer
- Fix documentation
paradox 0.11.0
Description Handling parameter spaces
- Minor Bug Fixes