mlr3 0.17.1

• Remove data_prototype when resampling from learner$state to reduce memory consumption.
• Reduce number of threads used by data.table and BLAS to 1 when running resample() or benchmark() in parallel.
• Optimize runtime of resample() and benchmark() by reducing the number of hashing operations.

mlr3 0.17.0

• Learners cannot be added to the HotstartStack anymore when the model is missing.
• Learners bellow the hotstart_threshold are not added to the HotstartStack anymore.
• The learner$state$train_time in hotstarted learners is now only the time of the last training.
• Added debug messages to the hotstart stack.
• Fixed bug where the HotstartStack did not work with column roles set in the task.
• The design of benchmark() can now include parameter settings.
• Speed up resampling by removing unnecessary calls to packageVersion().
• Fix boston housing data set.
• Export generic function col_info to allow adding new methods for backends.
• Task printer includes row roles now.
• Add "mlr3.exec_chunk_bins" option to split the resampling iterations into a number of bins.

mlr3 0.16.1

• Function data.table() is now re-exported.
• Fixed a test which randomly failed.
• Improved documentation.
• Add encapsulation mode "try", which works similar to "none" but captures errors

mlr3 0.16.0

• Added argument paired to benchmark_grid() function, which can be used to create a benchmark design, where
  resamplings have been instantiated on tasks.
• Added S3 method for ResultData for as_resample_result() converter.
• Added S3 method for list for as_resample_result() converter.
• The featureless classification learner now returns proper probabilities
  (#918).

mlr3 0.15.0

• Many returned tables are now assigned a class for a print method to make the output
  more readable.
• Fixed some typos

mlr3 0.14.1

• 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() for data.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.

mlr3 0.14.0

• Added multiclass measures: mauc_aunu, mauc_aunp, mauc_au1u, mauc_au1p.
• Measure classif.costs does not require a Task 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 package future.apply.
• Fixed runtime measures depending on specific predict types (#832).
• Added head() and tail() methods for Task.
• Improved printing of multiple objects.

mlr3 0.13.3

• Most objects now have a new (optional) field label, i.e. Task,
  TaskGenerator, Learner, Resampling, and Measure.
• as.data.table() methods for objects of class Dictonary have been extended
  with additional columns.
• as_task_classif.formula() and as_task_regr.formula() now remove additional
  atrributes attached to the data which caused some some learners to break.
• Packages are now loaded prior to calling the $train() and $predict()
  methods of a Learner. This ensures that package loading errors are properly
  propagated and not affected by encapsulation (#771).

mlr3 0.13.2

• Setting a fallback learner for a learner with encapsulation in its default
  settings now automatically sets encapsulation to "evaluate" (#763).
• as_task_classif() and as_task_regr() now support the construction of tasks
  using the formula interface, e.g. as_task_regr(mpg ~ ., data = mtcars)
  (#761).
• The row role "validation" has been renamed to "holdout".
  In the next release, mlr3 will start switching to the now more common terms
  "train"/"validation" instead of "train"/"test" for the sets created
  during resampling.