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Calls mda::mars from package mda.

Dictionary

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

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

Meta Information

  • Task type: “regr”

  • Predict Types: “response”

  • Feature Types: “integer”, “numeric”

  • Required Packages: mlr3extralearners, mda

Parameters

IdTypeDefaultLevelsRange
degreeinteger1\([1, \infty)\)
nkinteger-\([1, \infty)\)
penaltynumeric2\([0, \infty)\)
threshnumeric0.001\([0, \infty)\)
prunelogicalTRUETRUE, FALSE\((-\infty, \infty)\)
trace.marslogicalFALSETRUE, FALSE\((-\infty, \infty)\)
forward.steplogicalFALSETRUE, FALSE\((-\infty, \infty)\)

See also

Author

sumny

Super classes

mlr3::Learner -> mlr3::LearnerRegr -> LearnerRegrMars

Methods

Inherited methods


Method new()

Creates a new instance of this R6 class.

Usage


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerRegrMars$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (requireNamespace("mda", quietly = TRUE)) {
  learner = mlr3::lrn("regr.mars")
  print(learner)

  # available parameters:
  learner$param_set$ids()
}
#> <LearnerRegrMars:regr.mars>
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3extralearners, mda
#> * Predict Type: response
#> * Feature types: integer, numeric
#> * Properties: -
#> [1] "degree"       "nk"           "penalty"      "thresh"       "prune"       
#> [6] "trace.mars"   "forward.step"