These learners provide an interface to the wrapper functions, screening algorithms, and combination methods provided by the SuperLearner package. These components add support for a range of algorithms not currently implemented natively in sl3.

Lrnr_pkg_SuperLearner - Interface for SuperLearner wrapper functions. Use SuperLearner::listWrappers("SL") for a list.

Use SuperLearner::listWrappers("method") for a list of options.

Use SuperLearner::listWrappers("screen") for a list of options.


R6Class object.


Learner object with methods for training and prediction. See Lrnr_base for documentation on learners.



The wrapper function to use.


Currently not used.

Common Parameters

Individual learners have their own sets of parameters. Below is a list of shared parameters, implemented by Lrnr_base, and shared by all learners.


A character vector of covariates. The learner will use this to subset the covariates for any specified task


A variable_type object used to control the outcome_type used by the learner. Overrides the task outcome_type if specified


All other parameters should be handled by the invidual learner classes. See the documentation for the learner class you're instantiating