Changelog

mlr3extralearners 0.5.13

• Fix categorical_features in {lightgbm} learners

mlr3extralearners 0.5.12

• Patch for lightgbm updates

mlr3extralearners 0.5.11

• Add option to not open files with create_learner

mlr3extralearners 0.5.10

• Added params ignored_features and one_hot_max_size to classif.catboost

mlr3extralearners 0.5.9

• Fixed bug that didn’t allow C parameter to be set for nu-regression

mlr3extralearners 0.5.8

• Add regr.rvm and classif.lssvm

mlr3extralearners 0.5.7

• Introduced new custom hyperparameters for randomForestSRC::rfsrc(), partykit::cforest() and obliqueRSF::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 0.5.5

• Bugfix regr.gausspr

mlr3extralearners 0.5.4

• Add regr.gausspr and classif.gausspr from kernlab::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 0.4.9

• Minor internal changes

mlr3extralearners 0.4.8

• Added LearnerRegrCubist and LearnerRegrMars

mlr3extralearners 0.4.7

• Moved nnet learners to mlr3learners

mlr3extralearners 0.4.6

• Updates default cores for rfsrc learners to 1

mlr3extralearners 0.4.5

• Fix RWeka tests (stochastic failures, implementation unaffected)

mlr3extralearners 0.4.3

• Add support for custom families in all remaining mboost learners

mlr3extralearners 0.4.2

• Fix broken partykit tests

mlr3extralearners 0.4.0

• Added LearnerRegrGam and LearnerClassifGam with keys regr.gam and classif.gam from package mgcv.

mlr3extralearners 0.3.6

• surv.coxboost now uses the GitHub version instead of CRAN (archived)

mlr3extralearners 0.3.4

• Add support for custom families to regr.glmboost

mlr3extralearners 0.3.1

• surv.svm now supports all feature types

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: https://github.com/mlr-org/mlr3proba/issues/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

• Initial release. mlr3extralearners contains all learners from the mlr3learners organisation, which is now archived.