| SLLearner_cfg {tidyhte} | R Documentation | 
Configuration of SuperLearner Submodel
Description
SLLearner_cfg is a configuration class for a single
sublearner to be included in SuperLearner. By constructing with a named list
of hyperparameters, this configuration allows distinct submodels
for each unique combination of hyperparameters. To understand what models
and hyperparameters are available, examine the methods listed in
SuperLearner::listWrappers("SL").
Public fields
- model_name
- The name of the model as passed to - SuperLearnerthrough the- SL.libraryparameter.
- hyperparameters
- Named list from hyperparameter name to a vector of values that should be swept over. 
Methods
Public methods
Method new()
Create a new SLLearner_cfg object with specified model name and hyperparameters.
Usage
SLLearner_cfg$new(model_name, hp = NULL)
Arguments
- model_name
- The name of the model as passed to - SuperLearnerthrough the- SL.libraryparameter.
- hp
- Named list from hyperparameter name to a vector of values that should be swept over. Hyperparameters not included in this list are left at their SuperLearner default values. 
Returns
A new SLLearner_cfg object.
Examples
SLLearner_cfg$new("SL.glm")
SLLearner_cfg$new("SL.gam", list(deg.gam = c(2, 3)))
Method clone()
The objects of this class are cloneable with this method.
Usage
SLLearner_cfg$clone(deep = FALSE)
Arguments
- deep
- Whether to make a deep clone. 
Examples
## ------------------------------------------------
## Method `SLLearner_cfg$new`
## ------------------------------------------------
SLLearner_cfg$new("SL.glm")
SLLearner_cfg$new("SL.gam", list(deg.gam = c(2, 3)))