Changelog

Source: NEWS.md

mlr3learners 0.4.3 Unreleased

mlr3learners 0.4.2 2020-11-11

  • Fixed a bug in the survival random forest LearnerSurvRanger.

mlr3learners 0.4.1 2020-10-07

  • Disabled some glmnet tests on solaris.
  • Removed dependency on orphaned package bibtex.

mlr3learners 0.4.0 2020-09-25

  • Fixed a potential label switch in classif.glmnet and classif.cv_glmnet with predict_type set to "prob" (#155).
  • Fixed learners from package glmnet to be more robust if the order of features has changed between train and predict.

mlr3learners 0.3.0 2020-08-29

  • The $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.
  • Compact in-memory representation of R6 objects to save space when saving mlr3 objects via saveRDS(), serialize() etc.
  • glmnet learners: penalty.factor is a vector param, not a ParamDbl (#141)
  • glmnet: Add params mxitnr and epsnr from glmnet v4.0 update
  • Add learner surv.glmnet (#130)
  • Suggest package mlr3proba (#144)
  • Add learner surv.xgboost (#135)
  • Add learner surv.ranger (#134)

mlr3learners 0.2.0 2020-04-22

  • 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 Unreleased

  • 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 2020-02-10

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

mlr3learners 0.1.5 2019-11-25

  • 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 2019-10-29

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

mlr3learners 0.1.3 2019-09-17

  • 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 2019-08-26

  • Maintenance release.

mlr3learners 0.1.1 2019-08-05

  • Initial upload to CRAN.