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mlr3extralearners 0.5.37

  • Improve docs and change doc layout
  • Fix typo in man-roxygen templates
  • Port mlr3proba learners (mlr3proba is no longer on CRAN)
  • Exclude relevant files in precommit

mlr3extralearners 0.5.36

  • Add missing 'threads' tag to respective parameters.

mlr3extralearners 0.5.35

  • Full installatio in workflow 'test_selection' (is faster than the previous approach, where selected packages were installed from CRAN)

mlr3extralearners 0.5.34

  • remove explicit mlr3misc:: (is imported)

mlr3extralearners 0.5.33

  • consistency: Use params in train and predict calls, even in learners that currently don't have predict / train params. This allows easier correction of parameters by users.

mlr3extralearners 0.5.32

  • chore: add new parameters for kde and rfsrc

  • temporarily disable feat_all test for obliqeRSF (failed in $score() stage, because issue only happened in CI and could not be reproduced

mlr3extralearners 0.5.31

  • Many non-standard tags were included in the learners, these are removed
  • Some bugs in learners were fixed (survival rfsrc: "estimator" was incorrectly handled in .predict)
  • Minor refactorings in train methods of learners
  • Avoid partial argument matching: Some learners used "tag = ..." instead of the correct "tags = ..."

mlr3extralearners 0.5.30

  • Revert to using mlr3proba and survivalmodels CRAN version

mlr3extralearners 0.5.29

  • Change in vignette

mlr3extralearners 0.5.28

  • update randomForestSRC

mlr3extralearners 0.5.27

  • Update learner status page

mlr3extralearners 0.5.26

  • Fixed survivalmodel learners

mlr3extralearners 0.5.25

  • Introduce parameter early_stopping_split for lightgbm learners
  • Tidy description of R package
  • Udpate NEWS.md for previous releases

mlr3extralearners 0.5.24

  • Don't allow integer for density estimator dens.plug

mlr3extralearners 0.5.23

  • Fix bug in lightgbm

mlr3extralearners 0.5.22

  • Style package using the mlr3 style

mlr3extralearners 0.5.21

  • Update files for creation of new learner
  • Fixes regarding create_learner
  • CI modifications

mlr3extralearners 0.5.20

  • Fix all parameter tests (run_paramtest was updated in mlr3 in November 2021)
  • paramtests were moved from inst/paramtest to tests/testthat
  • Change in the CI files: parameter tests and learner tests are now run together
  • formatting and other minor corrections

mlr3extralearners 0.5.19

  • Provide correct range for neighors argument for Cubist

mlr3extralearners 0.5.18

  • Allow integer as feature types for RWeka learners
  • Correction of RWeka tests

mlr3extralearners 0.5.17

  • Improve vignette

mlr3extralearners 0.5.16

  • Fix bug in AdaBoostM1 (control arg)

mlr3extralearners 0.5.15

  • Change in maintainer

mlr3extralearners 0.5.14

  • Fix bug regarding Weka control args.

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

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: 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

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