Comments (1)
jeremyrcoyle
commented on August 16, 2024
Implementing this functionality would make it impossible to construct a learner that takes one argument that is a list, because it would be impossible to distinguish between a list that contains all the arguments and a list that is meant as the first argument. The best way to construct a learner from a named list of arguments would be to do do.call(make_learner, c(learner_class=Lrnr_codensier, lrnrs_args_list))
from sl3.
Related Issues (20)
- Add MAE loss function HOT 2
- Add count/nonnegative outcome variable type to sl3 and poisson family supporting learner properties HOT 2
- formula argument for learner clashes with formula argument of the internal learning routine (e.g. GAM) HOT 2
- documentation improvements
- Allowed argument for earth not being passed appropriately HOT 1
- Error : No newoffset provided for prediction, yet offset used in fit of glmnet HOT 1
- R 4.0 dependency (stringsAsFactors) HOT 3
- Devel install error HOT 4
- When loading the sl3 package, this error gets reported... HOT 7
- Predicting from `Lrnr_sl` HOT 3
- Example for `Lrnr_cv_selector` is not working HOT 3
- Delayed learner fit does not yield same result as regular fit when `Lrnr_randomForest` is used HOT 1
- `Lrnr_cv` predictions broken HOT 2
- Stratify folds by sparse outcome - question HOT 3
- Using sl3 fits in tmle3 HOT 2
- Lrnr_glmnet bug HOT 1
- sl3 CV split with rare events HOT 1
- sl3 presentation on website currently returns 404 error HOT 1
- chain_fold not defined for Lrnr_base
- installation problem HOT 5
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