MachineShop: GBMModel – R documentation

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GBMModel

Generalized Boosted Regression Model

Fits generalized boosted regression models.

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

`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.

Response Types:: factor, numeric, PoissonVariate, Surv
Automatic Tuning of Grid Parameters:: n.trees, interaction.depth, shrinkage*, n.minobsinnode*

* included only in randomly sampled grid points

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

MLModel class object.

## Requires prior installation of suggested package gbm to run

fit(Species ~ ., data = iris, model = GBMModel)

Machine Learning Models and Tools

v2.8.0

GPL-3

Authors

Brian J Smith [aut, cre]

Initial release

2021-04-16