MachineShop (version 1.1.0)

SuperModel: Super Learner Model

Description

Fit a super learner model to predictions from multiple base learners.

Usage

SuperModel(..., model = GBMModel, control = CVControl,
  all_vars = FALSE)

Arguments

...

MLModel objects to serve as base learners.

model

MLModel object, constructor function, or character string naming a constructor function to serve as the super model.

control

MLControl object, control function, or character string naming a control function defining the resampling method to be employed for the estimation of base learner weights.

all_vars

logical indicating whether to include the original predictor variables in the super model.

Value

SuperModel class object that inherits from MLModel.

Details

Response Types:

factor, numeric, ordered, Surv

References

van der Lann, M.J., Hubbard A.E. (2007) Super Learner. Statistical Applications in Genetics and Molecular Biology, 6(1).

See Also

fit, resample, tune

Examples

# NOT RUN {
library(MASS)

model <- SuperModel(GBMModel, SVMRadialModel, GLMNetModel(lambda = 0.01))
modelfit <- fit(medv ~ ., data = Boston, model = model)
predict(modelfit, newdata = Boston)

# }