mlr_learners_classif.liblinearl2l1svc.Rd
Calls LiblineaR::LiblineaR from package LiblineaR.
Calls LiblineaR::LiblineaR()
with type = 3
.
This Learner can be instantiated via the
dictionary mlr_learners or with the associated
sugar function lrn()
:
mlr_learners$get("classif.liblinearl2l1svc") lrn("classif.liblinearl2l1svc")
Packages: LiblineaR
Predict Types: response
Feature Types: numeric
Properties: multiclass, twoclass
epsilon
:
Actual default: 0.01
Adjusted default: 0.1
Reason for change: Param depends on param "type" which is handled internally by choosing the mlr3 learner. The default is set to the actual default of the respective "type".
be-marc
mlr3::Learner
-> mlr3::LearnerClassif
-> LearnerClassifLiblineaRL2L1SVC
new()
Creates a new instance of this R6 class.
LearnerClassifLiblineaRL2L1SVC$new()
clone()
The objects of this class are cloneable with this method.
LearnerClassifLiblineaRL2L1SVC$clone(deep = FALSE)
deep
Whether to make a deep clone.
# stop example failing with warning if package not installed learner = suppressWarnings(mlr3::lrn("classif.liblinearl2l1svc")) print(learner)#> <LearnerClassifLiblineaRL2L1SVC:classif.liblinearl2l1svc> #> * Model: - #> * Parameters: epsilon=0.1 #> * Packages: LiblineaR #> * Predict Type: response #> * Feature types: numeric #> * Properties: multiclass, twoclass# available parameters: learner$param_set$ids()#> [1] "cost" "epsilon" "bias" "cross" "verbose" "wi" "findC" #> [8] "useInitC"