mlr3learners 0.2.0

• Split {glmnet} learner into cv_glmnet and glmnet (#99)
• {glmnet} learners: Add predict.gamma and newoffset 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).
• There is now a vignette “Additional Learners” listing all external learners which live in the mlr3learners organization. See mlr3learners.drat for easy installation.

mlr3learners 0.1.6.9000

• Added learner classif.multinom from package nnet.
• Learners regr.lm and classif.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)

XGBoost

• Add parameter `“interaction_constraints” (#95)

mlr3learners 0.1.6

• Added missing feature type logical() to multiple learners.

mlr3learners 0.1.5

• 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 and classif.svm.
• glmnet: Added relax parameter (v3.0)
• xgboost: Updated parameters for v0.90.0.2

mlr3learners 0.1.4

• Fixed a bug in *.xgboost and *.svm which was triggered if columns were reordered between $train() and $predict().

mlr3learners 0.1.3

• 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

mlr3learners 0.1.2

• Maintenance release.

mlr3learners 0.1.1

• Initial upload to CRAN.