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 SuperLearner through the SL.library parameter.

hyperparameters

Named list from hyperparameter name to a vector of values that should be swept over.

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 SuperLearner through the SL.library parameter.

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$new("SL.glm")
#> <SLLearner_cfg>
#>   Public:
#>     clone: function (deep = FALSE) 
#>     hyperparameters: NULL
#>     initialize: function (model_name, hp = NULL) 
#>     model_name: SL.glm
SLLearner_cfg$new("SL.gam", list(deg.gam = c(2, 3)))
#> <SLLearner_cfg>
#>   Public:
#>     clone: function (deep = FALSE) 
#>     hyperparameters: list
#>     initialize: function (model_name, hp = NULL) 
#>     model_name: SL.gam