SLLearner_cfg: Configuration of SuperLearner Submodel

In tidyhte: Tidy Estimation of Heterogeneous Treatment Effects

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 SuperLearner through the SL.library parameter.

hyperparameters

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

Methods

Public methods

• SLLearner_cfg$new()

• SLLearner_cfg$clone()

---

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$new("SL.glm")
SLLearner_cfg$new("SL.gam", list(deg.gam = c(2, 3)))

tidyhte documentation built on Aug. 14, 2023, 5:08 p.m.