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.
bbotk 0.5.4
Description Black-Box Optimization Toolkit
- feat: Add
OptimizerFocusSearch
that performs a focusing random search.
mlr3 0.14.0
Description Machine Learning in R - Next Generation
- Added multiclass measures:
mauc_aunu
,mauc_aunp
,mauc_au1u
,mauc_au1p
. - Measure
classif.costs
does not require aTask
anymore. - New converter:
as_task_unsupervised()
- Refactored the task types in
mlr_reflections
.
mlr3 0.13.4
- Added new options for parallelization (
"mlr3.exec_random"
and"mlr3.exec_chunk_size"
). These options are passed down to the respective map functions in packagefuture.apply
. - Fixed runtime measures depending on specific predict types (#832).
- Added
head()
andtail()
methods forTask
. - Improved printing of multiple objects.
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
mlr3cluster 0.1.4
Description Cluster Extension for ‘mlr3’
- code refactoring
mlr3data 0.6.1
Description Collection of Machine Learning Data Sets for ‘mlr3’
Fixed documentation and CRAN notes.
Added simplified version of the penguins data set as
penguins_simple
.Added labels to data sets.
mlr3db 0.5.0
Description Data Base Backend for ‘mlr3’
- Support for parquet files as Backend via DuckDB.
- New converter
as_duckdb_backend()
.
mlr3fairness 0.3.1
Description Fairness Auditing and Debiasing for ‘mlr3’
- Minor update to improve stability of unit tests and vignette building on CRAN.
mlr3filters 0.6.0
Description Filter Based Feature Selection for ‘mlr3’
- Add
FilterCarSurvScore
(#120, (mllg?)) - Use featureless learner instead of rpart as default learner for
FilterImportance
andFilterPerformance
(#124) - Add documentation for PipeOpFilter
- Add mlr3pipelines examples to help pages (#135, (sebffischer?))
- Add
label
arg toFilter
class (#121, (mllg?))
mlr3fselect 0.7.2
Description Feature Selection for ‘mlr3’
- docs: Re-generate rd files with valid html.
mlr3hyperband 0.4.2
Description Hyperband for ‘mlr3’
- docs: Re-generate rd files with valid html.
mlr3learners 0.5.4
Description Recommended Learners for ‘mlr3’
- Added
regr.nnet
learner. - Removed the option to use weights in
classif.log_reg
. - Added
default_values()
function for ranger and svm learners. - Improved documentation.
mlr3measures 0.5.0
Description Performance Measures for ‘mlr3’
- Added some observation-wise loss functions:
ae
,ape
,se
,sle
, andzero_one
,
mlr3oml 0.6.0
Description Connector Between ‘mlr3’ and ‘OpenML’
Features
- Add R6 classes for
OMLCollection
,OMLRun
,OMLFlow
. - Added function
benchmark_grid_oml
that allows for easier creation of benchmark designs from OpenML task-resampling pairs. - Added sugar functions
oml_flow
,oml_data
,oml_task
,oml_run
,oml_collection
for all OpenML objects. - Conversion from OpenML to mlr3 objects is now only possible with the usual s3-converters
as_<object>
. This improves consistency by ensuring that the subcomponents of OpenML objects are always OpenML objects and not suddenly mlr3 objects. - Added more converter functions:
as_learner
,as_resample_result
,as_data_backend
,as_benchmark_result
. - Added support for parquet files that were recently introduced on OpenML. The global option
mlr3oml.parquet
can be used to enable or disable this. By default it isFALSE
. This is implemented via the duckdb backend frommlr3db
. - Support to use the OpenML test server. This can be globally enabled using the option
mlr3oml.test_server
or individually for objects. Options to globally define an API-key for the test server are through the environment variableTESTOPENMLAPIKEY
or the optionmlr3oml.test_api_key
Fixes
- Removed support for survival tasks as mlr3proba is no longer on CRAN
- OpenML tasks can now also be filtered according to the task type
Other
- Implement an arff writer and remove the arff dependency, therefore also removing the option
"farff"
as themlr3oml.arff_parser
- Increment the cache version number due to changes in the cache structure: This will flush the previous cache folder.
- Simplified the code structure by adding
OMLObject
class from which all other OpenML objects likeOMLData
,OMLTask
inherit.
mlr3pipelines 0.4.2
Description Preprocessing Operators and Pipelines for ‘mlr3’
- Documentation: Clarified
PipeOpHistBin
operation. - Documentation: Fixed
PipeOpPCA
documentation ofcenter
default. - Added
$label
active binding, setting it to thehelp()
-page title by default. - Made tests compatible with upcoming mlr3misc update.
mlr3spatial 0.2.1
Description Support for Spatial Objects Within the ‘mlr3’ Ecosystem
- fix: add
"space"
and"time"
column role from mlr3spatiotempcv
mlr3spatial 0.2.0
- BREAKING CHANGE:
TaskClassifST
andTaskRegrST
are used to train a learner with spatial data. The new tasks unify the work with mlr3spatiotempcv. - BREAKING CHANGE: Raster objects cannot be used to create tasks for training anymore.
- BREAKING CHANGE:
TaskUnsupervised
is used to predict on rasters objects now. The new task type is more convenient for data without a response. - feat: Add
as_task_regr_st()
andas_task_classif_st()
from spatial objects. - feat: Add
as_task_unsupervised()
from raster objects. - feat: Task
leipzig
with land cover target. - feat:
data("leipzig")
loads ansf
object with land cover in Leipzig. - feat: GeoTIFF and GeoPackage of Leipzig in
extdata
folder. - refactor: Vector data is handled with
DataBackendDataTable
now andDataBackendVector
is removed. - BREAKING CHANGE:
DataBackendRaster
cannot be created fromRasterLayer
objects anymore. - fix:
spatial_predict()
returned an unnamed response. - fix:
spatial_predict()
wrote predictions to the wrong cell. - BREAKING CHANGE: Remove
demo_raster()
,demo_stack_spatraster()
,demo_stack_rasterbrick()
anddemo_rasterbrick()
functions. - feat: Prediction layer contains
NA
at raster cells withNA
values in one or more feature layers.
mlr3tuning 0.14.0
Description Tuning for ‘mlr3’
- feat: Add option
evaluate_default
to evaluate learners with hyperparameters set to their default values. - refactor: From now on, the default of
smooth
isFALSE
forTunerGenSA
.
mlr3viz 0.5.10
Description Visualizations for ‘mlr3’
- Improved documentation.
- Make checks run without suggested packages.
paradox 0.10.0
Description Define and Work with Parameter Spaces for Complex Algorithms
- Reset
.has_extra_trafo
toFALSE
when trafo is set toNULL
. rd_info.ParamSet
collapses vector with"\n"
due changes in roxygen 7.2.0- Add method
set_values()
to conveniently add parameter values.