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Support Vector Regression. Calls kernlab::ksvm() from kernlab.

Dictionary

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

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

Meta Information

  • Task type: “regr”

  • Predict Types: “response”

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

  • Required Packages: mlr3, mlr3extralearners, kernlab

Parameters

IdTypeDefaultLevelsRange
scaledlogicalTRUETRUE, FALSE-
typecharactereps-svreps-svr, nu-svr, eps-bsvr-
kernelcharacterrbfdotrbfdot, polydot, vanilladot, laplacedot, besseldot, anovadot-
Cnumeric1\((-\infty, \infty)\)
nunumeric0.2\([0, \infty)\)
epsilonnumeric0.1\((-\infty, \infty)\)
cacheinteger40\([1, \infty)\)
tolnumeric0.001\([0, \infty)\)
shrinkinglogicalTRUETRUE, FALSE-
sigmanumeric-\([0, \infty)\)
degreeinteger-\([1, \infty)\)
scalenumeric-\([0, \infty)\)
orderinteger-\((-\infty, \infty)\)
offsetnumeric-\((-\infty, \infty)\)
na.actionuntypedna.omit-
fitlogicalTRUETRUE, FALSE-

References

Karatzoglou, Alexandros, Smola, Alex, Hornik, Kurt, Zeileis, Achim (2004). “kernlab-an S4 package for kernel methods in R.” Journal of statistical software, 11(9), 1--20.

See also

Author

mboecker

Super classes

mlr3::Learner -> mlr3::LearnerRegr -> LearnerRegrKSVM

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

LearnerRegrKSVM$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

learner = mlr3::lrn("regr.ksvm")
print(learner)
#> <LearnerRegrKSVM:regr.ksvm>: Support Vector Machine
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3extralearners, kernlab
#> * Predict Type: response
#> * Feature types: logical, integer, numeric, character, factor, ordered
#> * Properties: weights

# available parameters:
learner$param_set$ids()
#>  [1] "scaled"    "type"      "kernel"    "C"         "nu"        "epsilon"  
#>  [7] "cache"     "tol"       "shrinking" "sigma"     "degree"    "scale"    
#> [13] "order"     "offset"    "na.action" "fit"