mlr3extralearners 0.3.0

• Added LearnerRegrLightGBM and LearnerClassifLightGBM with keys regr.lightgbm and classif.lightgbm respectively. Copied from mlr3learners.lightgbm
• LearnerRegrLiblineaRX and LearnerClassifLiblineaRX deprecated in favour of only two learners (LearnerRegrLiblineaR and LearnerClassLiblineaR) 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 from surv.parametric as it is unclear what this was previously predicting.
• Added type = "tobit" for dist = "gaussian" so predictions can correspond with survival::survreg.
• Added LearnerRegrGlm with the unique key regr.glm from package stats, which allows users to change the family hyperparameter when fitting generalized linear regression models.
• Minor internal changes
• Removed keeptrees parameter from classif.bart as this is forced internally
• Fixed incorrect response and probability predictions in classif.bart
• Added hyper-parameters to classif.earth and regr.earth
• Added se predict type to regr.earth
• Fixed predictions in regr.knn and classif.knn

mlr3extralearners 0.1.3

• mlr3proba moved to Suggests
• 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 and distr computation of all survival learners

mlr3extralearners 0.1.1

• Patch for bugs in surv learners that were reversing the order of crank, see this issue for full details: mlr-org/mlr3proba#165
• response is no longer returned by surv.mboost, surv.blackboost, surv.glmboost, surv.gamboost or surv.parametric
• Bugfix in surv.parametric with ph form
• Bugfix in survivalmodelslearners which weren't returning distr
• surv.coxboost and surv.coxboost_cv can now only handle integer and numeric 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.