Releases · mlr-org/mlr3

Added support for "marshal" property, which allows learners to process models so they can be serialized.
This happens automatically during resample() and benchmark().
Encapsulation methods use the same RNG state now.
Fix missing values in default_values.Learner() function.
Encapsulated error messages are now printed with the lgr package.

Prepare compatibility with new paradox version.
feat: dictionary conversion of mlr_learners respects prototype arguments
recently added in mlr3misc
perf: skip unnecessary clone of learner's state in resample()

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.

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.

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

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).

Releases: mlr-org/mlr3