Releases: mlr-org/mlr3extralearners
Releases · mlr-org/mlr3extralearners
mlr3extralearners 0.3.1
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 0.1.2
- Fixes in
crank
anddistr
computation of all survival learners
mlr3extralearners 0.1.1
- Patch for bugs in
surv
learners that were reversing the order ofcrank
, see this issue for full details: mlr-org/mlr3proba#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.
mlr3extralearners 0.1.0
mlr3extralearners contains all learners from the mlr3learners organisation, which is now archived.