Changelog
mlr3extralearners 0.5.37
- Improve docs and change doc layout
- Fix typo in man-roxygen templates
- Port mlr3proba learners (mlr3proba is no longer on CRAN)
- Exclude relevant files in precommit
mlr3extralearners 0.5.35
- Full installatio in workflow ‘test_selection’ (is faster than the previous approach, where selected packages were installed from CRAN)
mlr3extralearners 0.5.33
- consistency: Use params in train and predict calls, even in learners that currently don’t have predict / train params. This allows easier correction of parameters by users.
mlr3extralearners 0.5.32
chore: add new parameters for kde and rfsrc
temporarily disable feat_all test for obliqeRSF (failed in $score() stage, because issue only happened in CI and could not be reproduced
mlr3extralearners 0.5.31
- Many non-standard tags were included in the learners, these are removed
- Some bugs in learners were fixed (survival rfsrc: “estimator” was incorrectly handled in .predict)
- Minor refactorings in train methods of learners
- Avoid partial argument matching: Some learners used “tag = …” instead of the correct “tags = …”
mlr3extralearners 0.5.25
- Introduce parameter
early_stopping_split
for lightgbm learners - Tidy description of R package
- Udpate NEWS.md for previous releases
mlr3extralearners 0.5.21
- Update files for creation of new learner
- Fixes regarding
create_learner
- CI modifications
mlr3extralearners 0.5.20
- Fix all parameter tests (run_paramtest was updated in mlr3 in November 2021)
- paramtests were moved from inst/paramtest to tests/testthat
- Change in the CI files: parameter tests and learner tests are now run together
- formatting and other minor corrections
mlr3extralearners 0.5.18
- Allow integer as feature types for RWeka learners
- Correction of RWeka tests
mlr3extralearners 0.5.7
- Introduced new custom hyperparameters for
randomForestSRC::rfsrc()
,partykit::cforest()
andobliqueRSF::ORSF()
to conveniently tune hyperparameters whose upper limit depends on data dimensions.
mlr3extralearners 0.5.6
- Fix learners requiring distr6. distr6 1.6.0 now forced and param6 added to suggests
mlr3extralearners 0.5.4
- Add
regr.gausspr
andclassif.gausspr
fromkernlab::gausspr
mlr3extralearners 0.5.3
- Fixed bugs in catboost for classification
- Removed factor feature types from catboost
- Added
install_catboost
to make installation from catboost simpler
mlr3extralearners 0.5.2
Fixed learner tests # mlr3extralearners 0.5.1
Fixes bug in
base
parameter of {bart} learners
mlr3extralearners 0.5.0
- Deprecated liblinear learners now removed
- Internal changes to ParamSet representation
- checkmate now imported
mlr3extralearners 0.4.7
- Moved
nnet
learners to mlr3learners
mlr3extralearners 0.4.0
- Added
LearnerRegrGam
andLearnerClassifGam
with keysregr.gam
andclassif.gam
from packagemgcv
.
mlr3extralearners 0.3.0
- Added
LearnerRegrLightGBM
andLearnerClassifLightGBM
with keysregr.lightgbm
andclassif.lightgbm
respectively. Copied from mlr3learners.lightgbm -
LearnerRegrLiblineaRX
andLearnerClassifLiblineaRX
deprecated in favour of only two learners (LearnerRegrLiblineaR
andLearnerClassLiblineaR
) with added hyper-parameters. Deprecated learners will be removed in v0.3.0. - Deprecated
classif.nnet
will be removed in v0.4.0. - Deprecated
liblinearX
will be removed in v0.4.0.
mlr3extralearners 0.2.0
-
dist = "logistic"
has been removed fromsurv.parametric
as it is unclear what this was previously predicting. - Added
type = "tobit"
fordist = "gaussian"
so predictions can correspond withsurvival::survreg
. - Added
LearnerRegrGlm
with the unique keyregr.glm
from packagestats
, which allows users to change thefamily
hyperparameter when fitting generalized linear regression models. - Minor internal changes
- Removed
keeptrees
parameter fromclassif.bart
as this is forced internally - Fixed incorrect response and probability predictions in
classif.bart
- Added hyper-parameters to
classif.earth
andregr.earth
- Added
se
predict type toregr.earth
- Fixed predictions in
regr.knn
andclassif.knn
mlr3extralearners 0.1.3
-
mlr3proba
moved toSuggests
-
install_learners
now additionally installs required mlr3 packages - Bugfix in
surv.parametric
occurring if feature names are switched between training and predicting - Deprecated
classif.nnet
, in the future please load from mlr3learners
mlr3extralearners 0.1.1
- Patch for bugs in
surv
learners that were reversing the order ofcrank
, see this issue for full details: https://github.com/mlr-org/mlr3proba/issues/165 -
response
is no longer returned bysurv.mboost
,surv.blackboost
,surv.glmboost
,surv.gamboost
orsurv.parametric
- Bugfix in
surv.parametric
withph
form - Bugfix in
survivalmodels
learners which weren’t returningdistr
-
surv.coxboost
andsurv.coxboost_cv
can now only handleinteger
andnumeric
feature types, previous automated internal coercions were inconsistent with mlr3 design.