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Calls kernlab::ksvm from package kernlab.

Dictionary

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

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

Meta Information

  • Task type: “classif”

  • Predict Types: “response”, “prob”

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

  • Required Packages: mlr3extralearners, kernlab

Parameters

IdTypeDefaultLevelsRange
scaledlogicalTRUETRUE, FALSE\((-\infty, \infty)\)
typecharacterC-svcC-svc, nu-svc, C-bsvc, spoc-svc, kbb-svc\((-\infty, \infty)\)
kernelcharacterrbfdotrbfdot, polydot, vanilladot, laplacedot, besseldot, anovadot\((-\infty, \infty)\)
Cnumeric1\((-\infty, \infty)\)
nunumeric0.2\([0, \infty)\)
cacheinteger40\([1, \infty)\)
tolnumeric0.001\([0, \infty)\)
shrinkinglogicalTRUETRUE, FALSE\((-\infty, \infty)\)
sigmanumeric-\([0, \infty)\)
degreeinteger-\([1, \infty)\)
scalenumeric-\([0, \infty)\)
orderinteger-\((-\infty, \infty)\)
offsetnumeric-\((-\infty, \infty)\)

See also

Author

mboecker

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifKSVM

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

LearnerClassifKSVM$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

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

  # available parameters:
  learner$param_set$ids()
}
#> <LearnerClassifKSVM:classif.ksvm>
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3extralearners, kernlab
#> * Predict Type: response
#> * Feature types: logical, integer, numeric, character, factor, ordered
#> * Properties: multiclass, twoclass, weights
#>  [1] "scaled"    "type"      "kernel"    "C"         "nu"        "cache"    
#>  [7] "tol"       "shrinking" "sigma"     "degree"    "scale"     "order"    
#> [13] "offset"