Learner that encapsulates the Super Learner algorithm. Fits metalearner on cross-validated predictions from learners. Then forms a pipeline with the learners.

Format

R6Class object.

Value

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

Parameters

learners

The "library" of learners to include

metalearner

The metalearner to be fit on predictions from the library.

If null, default_metalearner is used to construct a metalearner based on the outcome_type of the training task.
folds=NULL

An origami folds object. If NULL, folds from the task are used.

keep_extra=TRUE

Stores all sub-parts of the SL computation. When set to FALSE the resultant object has a memory footprint that is significantly reduced through the discarding of intermediary data structures.

...

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.

covariates

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

outcome_type

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

See also