- Added
survival:aft
objective tosurv.xgboost
- Removed hyperparameter
predict.all
from ranger learners (#172).
- Fixed stochastic test failures on solaris.
- Fixed
surv.ranger
, c.f. mlr-org/mlr3proba#165. - Added
classif.nnet
learner (moved from mlr3extralearners).
- Fixed a bug in the survival random forest
LearnerSurvRanger
.
- Disabled some
glmnet
tests on solaris. - Removed dependency on orphaned package
bibtex
.
- Fixed a potential label switch in
classif.glmnet
andclassif.cv_glmnet
withpredict_type
set to"prob"
(#155). - Fixed learners from package
glmnet
to be more robust if the order of features has changed between train and predict.
- The
$model
slot of the {kknn} learner now returns a list containing some information which is being used during the predict step. Before, the slot was empty because there is no training step for kknn. - Compact in-memory representation of R6 objects to save space when saving mlr3
objects via
saveRDS()
,serialize()
etc. - glmnet learners:
penalty.factor
is a vector param, not aParamDbl
(#141) - glmnet: Add params
mxitnr
andepsnr
from glmnet v4.0 update - Add learner
surv.glmnet
(#130) - Suggest package
mlr3proba
(#144) - Add learner
surv.xgboost
(#135) - Add learner
surv.ranger
(#134)
- Split glmnet learner into
cv_glmnet
andglmnet
(#99) - glmnet learners: Add
predict.gamma
andnewoffset
arg (#98) - We now test that all learners can be constructed without parameters.
- A new custom "Paramtest" which lives
inst/paramtest
was added. This test checks against the arguments of the upstream train & predict functions and ensures that all parameters are implemented in the respective mlr3 learner (#96). - A lot missing parameters were added to learners. See #96 for a complete list.
- Add parameter
interaction_constraints
to {xgboost} learners (#97).
- Added learner
classif.multinom
from packagennet
. - Learners
regr.lm
andclassif.log_reg
now ignore the global option"contrasts"
. - Add vignette
additional-learners.Rmd
listing all mlr3 custom learners - Move Learner*Glmnet to Learner*CVGlmnet and add Learner*Glmnet (without internal tuning) (#90)
- Add parameter
interaction_constraints
(#95)
- Added missing feature type
logical()
to multiple learners.
- Added parameter and parameter dependencies to
regr.glmnet
,regr.km
,regr.ranger
,regr.svm
,regr.xgboost
,classif.glmnet
,classif.lda
,classif.naivebayes
,classif.qda
,classif.ranger
andclassif.svm
. glmnet
: Addedrelax
parameter (v3.0)xgboost
: Updated parameters for v0.90.0.2
- Fixed a bug in
*.xgboost
and*.svm
which was triggered if columns were reordered between$train()
and$predict()
.
-
Changes to work with new
mlr3::Learner
API. -
Improved documentation.
-
Added references.
-
add new parameters of xgboost version 0.90.2
-
add parameter dependencies for xgboost
- Maintenance release.
- Initial upload to CRAN.