Calls LiblineaR::LiblineaR from package LiblineaR.

Details

Type of SVC depends on type argument:

  • 0 – L2-regularized logistic regression (primal)

  • 1 - L2-regularized L2-loss support vector classification (dual)

  • 3 - L2-regularized L1-loss support vector classification (dual)

  • 2 – L2-regularized L2-loss support vector classification (primal)

  • 4 – Support vector classification by Crammer and Singer

  • 5 - L1-regularized L2-loss support vector classification

  • 6 - L1-regularized logistic regression

  • 7 - L2-regularized logistic regression (dual)

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

Note that probabilistic predictions are only available for types 0, 6, and 7.

The default epsilon value depends on the type parameter, see LiblineaR::LiblineaR.

Dictionary

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

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

Traits

  • Packages: LiblineaR

  • Predict Types: response, prob

  • Feature Types: numeric

  • Properties: multiclass, twoclass

See also

Author

be-marc

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifLiblineaR

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClassifLiblineaR$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

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