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Calls LiblineaR::LiblineaR from package LiblineaR.

Details

Type of SVR depends on type argument:

  • type = 11 - L2-regularized L2-loss support vector regression (primal)

  • type = 12 – L2-regularized L2-loss support vector regression (dual)

  • type = 13 – L2-regularized L1-loss support vector regression (dual)

Dictionary

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

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

Meta Information

  • Task type: “regr”

  • Predict Types: “response”

  • Feature Types: “integer”, “numeric”

  • Required Packages: mlr3extralearners, LiblineaR

Parameters

IdTypeDefaultLevelsRange
typeinteger11\([11, 13]\)
costnumeric1\([0, \infty)\)
biasnumeric1\((-\infty, \infty)\)
svr_epsnumericNULL\([0, \infty)\)
crossinteger0\([0, \infty)\)
verboselogicalFALSETRUE, FALSE\((-\infty, \infty)\)
findClogicalFALSETRUE, FALSE\((-\infty, \infty)\)
useInitClogicalTRUETRUE, FALSE\((-\infty, \infty)\)

Custom mlr3 defaults

  • svr_eps:

    • Actual default: NULL

    • Adjusted default: 0.001

    • Reason for change: svr_eps is type dependent and the "type" is handled by the mlr3learner. The default value is set to th default of the respective "type".

See also

Author

be-marc

Super classes

mlr3::Learner -> mlr3::LearnerRegr -> LearnerRegrLiblineaR

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

LearnerRegrLiblineaR$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

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

  # available parameters:
  learner$param_set$ids()
}
#> <LearnerRegrLiblineaR:regr.liblinear>
#> * Model: -
#> * Parameters: svr_eps=0.001
#> * Packages: mlr3, mlr3extralearners, LiblineaR
#> * Predict Type: response
#> * Feature types: integer, numeric
#> * Properties: -
#> [1] "type"     "cost"     "bias"     "svr_eps"  "cross"    "verbose"  "findC"   
#> [8] "useInitC"