Releases · mlr-org/mlr3extralearners

Added surv.xgboost.cox and surv.xgboost.aft separate survival learners. distr prediction on the cox xgboost learner is now estimated via Breslow by default and aft xgboost has now in addition a response prediction (survival time)
Ported surv.parametric code to survivalmodels, changed type parameter to form to avoid conflict with survivalmodels's default parameter list
Fix: Replace hardcoded VectorDistributions from partykit and flexsurv survival learners with survival matrices (Matdist) (thanks to @bblodfon)
Feat: Add discrete parameter in surv.parametric learner to return Matdist survival predictions
Added method selected_features() to CoxBoost survival learners (thanks to @bblodfon)
Added the Random Planted Forest Learner (thanks to @jemus42)
re-added the catboost learner as it was requested (was previously removed
because of installation issues)
surv.ranger now receives parameters during $predict() (thanks to @jemus42)
Feature: Learner surv.bart was added (thanks to @bblodfon)
Parameters of lrn("surv.aorsf") were updated (thanks to @bcjaeger)
Various minor doc improvements
Added the distr predict type to the surv.cv_glmnet and surv.glmnet
learners (thanks to @bblodfon)
Feat: Added many new WEKA learners (thanks to @damirpolat)
Fix: I and F params from IBk learner are too interdependent (I can only be TRUE when F is FALSE and vice versa).
Combined them into one factor param weight that has two levels -- I and F.
Fix: U must be FALSE for S to be tunable in J48 learner.
Compatibility with upcoming 'paradox' release.