Releases: mlr-org/mlr3
Releases · mlr-org/mlr3
mlr3 0.19.0
- Added support for
"marshal"
property, which allows learners to process models so they can be serialized.
This happens automatically duringresample()
andbenchmark()
. - 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.
mlr3 0.18.0
- 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()
mlr3 0.17.2
- Skip new
data.table
tests on mac.
mlr3 0.17.1
- Remove
data_prototype
when resampling fromlearner$state
to reduce memory consumption. - Reduce number of threads used by
data.table
and BLAS to 1 when runningresample()
orbenchmark()
in parallel. - Optimize runtime of
resample()
andbenchmark()
by reducing the number of hashing operations.
mlr3 0.17.0
- Learners cannot be added to the
HotstartStack
anymore when the model is missing. - Learners bellow the
hotstart_threshold
are not added to theHotstartStack
anymore. - The
learner$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
ofbenchmark()
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
tobenchmark_grid()
function, which can be used to create a benchmark design, where
resamplings have been instantiated on tasks. - Added S3 method for
ResultData
foras_resample_result()
converter. - Added S3 method for
list
foras_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()
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.
mlr3 0.14.0
- 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
.