mlr_learners_classif.ksvm.Rd
Calls kernlab::ksvm from package kernlab.
This Learner can be instantiated via the
dictionary mlr_learners or with the associated
sugar function lrn()
:
mlr_learners$get("classif.ksvm") lrn("classif.ksvm")
Packages: kernlab
Predict Types: response, prob
Feature Types: logical, integer, numeric, character, factor, ordered
Properties: multiclass, twoclass, weights
mboecker
mlr3::Learner
-> mlr3::LearnerClassif
-> LearnerClassifKSVM
new()
Creates a new instance of this R6 class.
LearnerClassifKSVM$new()
clone()
The objects of this class are cloneable with this method.
LearnerClassifKSVM$clone(deep = FALSE)
deep
Whether to make a deep clone.
# stop example failing with warning if package not installed learner = suppressWarnings(mlr3::lrn("classif.ksvm")) print(learner)#> <LearnerClassifKSVM:classif.ksvm> #> * Model: - #> * Parameters: list() #> * Packages: kernlab #> * Predict Type: response #> * Feature types: logical, integer, numeric, character, factor, ordered #> * Properties: multiclass, twoclass, weights# available parameters: learner$param_set$ids()#> [1] "scaled" "type" "kernel" "C" "nu" "cache" #> [7] "tol" "shrinking" "sigma" "degree" "scale" "order" #> [13] "offset"