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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("classif.gamboost")
lrn("classif.gamboost")

Meta Information

  • Task type: “classif”

  • Predict Types: “response”, “prob”

  • Feature Types: “integer”, “numeric”, “factor”, “ordered”

  • Required Packages: mlr3extralearners, mboost

Parameters

IdTypeDefaultLevelsRange
baselearnercharacterbbsbbs, bols, btree\((-\infty, \infty)\)
dfbaseinteger4\((-\infty, \infty)\)
offsetnumericNULL\((-\infty, \infty)\)
familycharacterBinomialBinomial, AdaExp, AUC, custom\((-\infty, \infty)\)
custom.familylist-\((-\infty, \infty)\)
linkcharacterlogitlogit, probit\((-\infty, \infty)\)
typecharacteradaboostglm, adaboost\((-\infty, \infty)\)
mstopinteger100\((-\infty, \infty)\)
nunumeric0.1\((-\infty, \infty)\)
riskcharacterinbaginbag, oobag, none\((-\infty, \infty)\)
oobweightslistNULL\((-\infty, \infty)\)
tracelogicalFALSETRUE, FALSE\((-\infty, \infty)\)
stopinternlistFALSE\((-\infty, \infty)\)
na.actionlistfunction (object, ...) , UseMethod("na.omit")\((-\infty, \infty)\)

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::LearnerClassif -> LearnerClassifGAMBoost

Methods

Inherited methods


Method new()

Create a LearnerClassifGAMBoost object.


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClassifGAMBoost$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (requireNamespace("mboost", quietly = TRUE)) {
  learner = mlr3::lrn("classif.gamboost")
  print(learner)

  # available parameters:
  learner$param_set$ids()
}
#> <LearnerClassifGAMBoost:classif.gamboost>
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3extralearners, mboost
#> * Predict Type: response
#> * Feature types: integer, numeric, factor, ordered
#> * Properties: twoclass, weights
#>  [1] "baselearner"   "dfbase"        "offset"        "family"       
#>  [5] "custom.family" "link"          "type"          "mstop"        
#>  [9] "nu"            "risk"          "oobweights"    "trace"        
#> [13] "stopintern"    "na.action"