Calls LiblineaR::LiblineaR from package LiblineaR.

Details

Calls LiblineaR::LiblineaR() with type = 1 or type = 2.

If number of records > number of features, type = 2 is faster than type = 1 (Hsu et al. 2003).

The default for epsilon is set to match type = 2. If you change to type = 1 remember to eventually adjust the value for epsilon (default = 0.1).

Dictionary

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

mlr_learners$get("classif.liblinearl2l2svc")
lrn("classif.liblinearl2l2svc")

Traits

  • Packages: LiblineaR

  • Predict Types: response

  • Feature Types: numeric

  • Properties: multiclass, twoclass

See also

Author

be-marc

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifLiblineaRL2L2SVC

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClassifLiblineaRL2L2SVC$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClassifLiblineaRL2L2SVC$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("classif.liblinearl2l2svc")) print(learner)
#> <LearnerClassifLiblineaRL2L2SVC:classif.liblinearl2l2svc> #> * Model: - #> * Parameters: list() #> * Packages: LiblineaR #> * Predict Type: response #> * Feature types: numeric #> * Properties: multiclass, twoclass
# available parameters: learner$param_set$ids()
#> [1] "cost" "epsilon" "bias" "type" "cross" "verbose" "wi" #> [8] "findC" "useInitC"