NEWS.md
surv.ranger
, c.f. https://github.com/mlr-org/mlr3proba/issues/165.glmnet
tests on solaris.bibtex
.classif.glmnet
and classif.cv_glmnet
with predict_type
set to "prob"
(#155).glmnet
to be more robust if the order of features has changed between train and predict.$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.saveRDS()
, serialize()
etc.penalty.factor
is a vector param, not a ParamDbl
(#141)mxitnr
and epsnr
from glmnet v4.0 updatesurv.glmnet
(#130)mlr3proba
(#144)surv.xgboost
(#135)surv.ranger
(#134)cv_glmnet
and glmnet
(#99)predict.gamma
and newoffset
arg (#98)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)interaction_constraints
to {xgboost} learners (#97).classif.multinom
from package nnet
.regr.lm
and classif.log_reg
now ignore the global option "contrasts"
.additional-learners.Rmd
listing all mlr3 custom learnersinteraction_constraints
(#95)logical()
to multiple learners.regr.glmnet
, regr.km
, regr.ranger
, regr.svm
, regr.xgboost
, classif.glmnet
, classif.lda
, classif.naivebayes
, classif.qda
, classif.ranger
and classif.svm
.glmnet
: Added relax
parameter (v3.0)xgboost
: Updated parameters for v0.90.0.2*.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