Learner that encapsulates the Super Learner algorithm. Fits metalearner on cross-validated predictions from learners. Then forms a pipeline with the learners.
Learner object with methods for training and prediction. See
Lrnr_base for documentation on learners.
The "library" of learners to include
The metalearner to be fit on predictions from the library.
origami folds object. If
folds from the task are used.
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
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
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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.