StackedModel: Stacked Regression Model

In brian-j-smith/MachineShop: Machine Learning Models and Tools

Stacked Regression Model

Description

Fit a stacked regression model from multiple base learners.

Usage

StackedModel(
  ...,
  control = MachineShop::settings("control"),
  weights = numeric()
)

Arguments

...	model functions, function names, objects; other objects that can be coerced to models; or vector of these to serve as base learners.
control	control function, function name, or object defining the resampling method to be employed for the estimation of base learner weights.
weights	optional fixed base learner weights.

Details

Response types:

factor, numeric, ordered, Surv

Value

StackedModel class object that inherits from MLModel.

References

Breiman, L. (1996). Stacked regression. Machine Learning, 24, 49-64.

See Also

fit, resample

Examples

## Requires prior installation of suggested packages gbm and glmnet to run

model <- StackedModel(GBMModel, SVMRadialModel, GLMNetModel(lambda = 0.01))
model_fit <- fit(sale_amount ~ ., data = ICHomes, model = model)
predict(model_fit, newdata = ICHomes)

brian-j-smith/MachineShop documentation built on Sept. 22, 2023, 10:01 p.m.