MachineShop (version 3.3.0)

GBMModel: Generalized Boosted Regression Model

Description

Fits generalized boosted regression models.

Usage

GBMModel(
  distribution = character(),
  n.trees = 100,
  interaction.depth = 1,
  n.minobsinnode = 10,
  shrinkage = 0.1,
  bag.fraction = 0.5
)

Arguments

distribution

optional character string specifying the name of the distribution to use or list with a component name specifying the distribution and any additional parameters needed. Set automatically according to the class type of the response variable.

n.trees

total number of trees to fit.

interaction.depth

maximum depth of variable interactions.

n.minobsinnode

minimum number of observations in the trees terminal nodes.

shrinkage

shrinkage parameter applied to each tree in the expansion.

bag.fraction

fraction of the training set observations randomly selected to propose the next tree in the expansion.

Value

MLModel class object.

Details

Response types:

factor, numeric, PoissonVariate, Surv

Automatic tuning of grid parameters:

n.trees, interaction.depth, shrinkage*, n.minobsinnode*

* excluded from grids by default

Default values and further model details can be found in the source link below.

See Also

gbm, fit, resample

Examples

# NOT RUN {
## Requires prior installation of suggested package gbm to run

fit(Species ~ ., data = iris, model = GBMModel)
# }
# NOT RUN {
# }