Model module to fit a generalized boosted regression (aka boosted regression
trees) model
GBM(.df, max.trees = 1000, interaction.depth = 5, shrinkage = 0.001)
Arguments
- .df
- Internal parameter, do not use in the workflow function.
.df is data frame that combines the occurrence
- max.trees
- The maximum number of trees to fit.
The number of trees is equivalent to the number of iterations and
the number of basis functions in the additive expansion. The optimal
number will be selected by cross-validation, but this sets an upper limit.
- interaction.depth
- The maximum depth of variable interactions.
1 implies an additive model, 2 implies a model with up to 2-way interactions,
etc.
- shrinkage
- a shrinkage parameter applied to each tree in the expansion.
Also known as the learning rate or step-size reduction.
Date submitted
2015-11-13
Data type
presence/absence
See also
Other model: BiomodModel,
LogisticRegression,
MachineLearn, MaxEnt,
MaxLike, MyMaxLike,
OptGRaF, QuickGRaF,
RandomForest,
StochasticLogisticRegression,
mgcv