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@sebffischer sebffischer released this 13 Oct 11:20
· 19 commits to main since this release
v1.2.0
1f7d5e9

New Features

  • New Learners:

    • LearnerCompRisksRandomForestSRC
    • LearnerSurvBlockForest
    • Learner{Classif,Regr,Surv}BlockForest
    • Learner{Classif,Regr}ExhaustiveSearch
    • LearnerClassifFastai
    • Learner{Classif,Regr}Penalized
    • Learner{Classif,Regr}Bst
    • LearnerClassifAdabag
    • LearnerClassifAdaBoosting
    • Learner{Classif,Regr}Evtree
    • LearnerClassifKnn
    • LearnerClassifRotationForest
    • LearnerRegrCrs
    • LearnerClassifStepPlr
    • LearnerClassifMda
    • LearnerClassifRferns
    • LearnerClassifNeuralnet
    • LearnerRegrBrnn
    • LearnerRegrBotorchSingleTaskGP
    • LearnerRegrBotorchMixedSingleTaskGP

  • Add new control_custom_fun parameter in surv.aorsf

  • New function learner_is_runnable() to check whether the
    required packages to train a learner are available.

  • Added selected_features property to RandomForestSRC learners (prediction doesn't work if vars.used = 'all.trees')

Bug fixes

  • Tests are now skipped when the suggested packages is not available.
    This will make local development much more convenient.
  • Removed parameters from RandomForestSRC learners that weren't used + optimized tests
  • Removed discrete parameter from surv.parametric, so that it is impossible to return distr6::VectorDistribution survival predictions (softly deprecated in [email protected])

Breaking Changes

  • All (extra) density learners are removed. These will be transferred to mlr3proba soon (see v0.8.2 or later).
  • The create_learner() generator was removed, because it was hard to maintain and boilerplate code in the age of LLMs is easy enough to write.
  • remove discrete parameter from surv.parametric, so that it is impossible to return distr6::VectorDistribution
    survival predictions (softly deprecated in [email protected])
  • classif.lightgbm now works with encapsulation with multiclass tasks
  • the package no longer re-exports lrn and lrns, which should anyway
    be available to the user as the package depends on mlr3, where these
    functions are defined.
  • Removed various learners:
    • randomPlantedForest was removed, because there is currently no way to
      save the model.
    • The deep learning methods from survivalmodels were removed, because
      they also cannot be saved and because the upstream package is archived.

Other

  • The package now imports withr
  • mlr3proba is now an import and no longer a suggested package.
  • mlr3cmprsk is added as an import.
  • The package no longer uses set.seed() in the tests and instead uses withr::local_seed()
    This means the auto tests will be stochastic like they should be.
  • The CI now checks that RCMD-check passes when suggested packages are not available.
  • distr6 dependency is removed. partykit survival learners use constant
    interpolation of the predicted Kaplan-Meier curves via survdistr::vec_interp()
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