Calls mboost::gamboost from package mboost.

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("regr.gamboost")
lrn("regr.gamboost")

Traits

  • Packages: mboost

  • Predict Types: response

  • Feature Types: integer, numeric, factor, ordered

  • Properties: weights

References

Bühlmann P, Yu B (2003). “Boosting With the L2 Loss.” Journal of the American Statistical Association, 98(462), 324–339. doi: 10.1198/016214503000125

See also

Author

be-marc

Super classes

mlr3::Learner -> mlr3::LearnerRegr -> LearnerRegrGAMBoost

Methods

Public methods

Inherited methods

Method new()

Create a LearnerRegrGAMBoost object.

Usage

LearnerRegrGAMBoost$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerRegrGAMBoost$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# stop example failing with warning if package not installed learner = suppressWarnings(mlr3::lrn("regr.gamboost")) print(learner)
#> <LearnerRegrGAMBoost:regr.gamboost> #> * Model: - #> * Parameters: list() #> * Packages: mboost #> * Predict Type: response #> * Feature types: integer, numeric, factor, ordered #> * Properties: weights
# available parameters: learner$param_set$ids()
#> [1] "baselearner" "dfbase" "offset" "family" #> [5] "custom.family" "nuirange" "d" "mstop" #> [9] "nu" "risk" "oobweights" "trace" #> [13] "stopintern" "na.action"