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Support vector machine for classification. Calls e1071::svm() from package e1071.

Dictionary

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

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

Meta Information

, * Task type: “classif”, * Predict Types: “response”, “prob”, * Feature Types: “logical”, “integer”, “numeric”, * Required Packages: mlr3, mlr3learners, e1071

Parameters

, |Id |Type |Default |Levels |Range |, |:---------------|:---------|:----------------|:-----------------------------------|:------------------------------------|, |cachesize |numeric |40 | |\((-\infty, \infty)\) |, |class.weights |untyped | | |- |, |coef0 |numeric |0 | |\((-\infty, \infty)\) |, |cost |numeric |1 | |\([0, \infty)\) |, |cross |integer |0 | |\([0, \infty)\) |, |decision.values |logical |FALSE |TRUE, FALSE |- |, |degree |integer |3 | |\([1, \infty)\) |, |epsilon |numeric |- | |\([0, \infty)\) |, |fitted |logical |TRUE |TRUE, FALSE |- |, |gamma |numeric |- | |\([0, \infty)\) |, |kernel |character |radial |linear, polynomial, radial, sigmoid |- |, |nu |numeric |0.5 | |\((-\infty, \infty)\) |, |scale |untyped |TRUE | |- |, |shrinking |logical |TRUE |TRUE, FALSE |- |, |tolerance |numeric |0.001 | |\([0, \infty)\) |, |type |character |C-classification |C-classification, nu-classification |- |

References

Cortes, Corinna, Vapnik, Vladimir (1995). “Support-vector networks.” Machine Learning, 20(3), 273--297. doi:10.1007/BF00994018 .

See also

Other Learner: mlr_learners_classif.cv_glmnet, mlr_learners_classif.glmnet, mlr_learners_classif.kknn, mlr_learners_classif.lda, mlr_learners_classif.log_reg, mlr_learners_classif.multinom, mlr_learners_classif.naive_bayes, mlr_learners_classif.nnet, mlr_learners_classif.qda, mlr_learners_classif.ranger, mlr_learners_classif.xgboost, mlr_learners_regr.cv_glmnet, mlr_learners_regr.glmnet, mlr_learners_regr.kknn, mlr_learners_regr.km, mlr_learners_regr.lm, mlr_learners_regr.ranger, mlr_learners_regr.svm, mlr_learners_regr.xgboost

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifSVM

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

LearnerClassifSVM$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (requireNamespace("e1071", quietly = TRUE)) {
  learner = mlr3::lrn("classif.svm")
  print(learner)

  # available parameters:
learner$param_set$ids()
}
#> <LearnerClassifSVM:classif.svm>
#> * Model: -
#> * Parameters: list()
#> * Packages: mlr3, mlr3learners, e1071
#> * Predict Type: response
#> * Feature types: logical, integer, numeric
#> * Properties: multiclass, twoclass
#>  [1] "cachesize"       "class.weights"   "coef0"           "cost"           
#>  [5] "cross"           "decision.values" "degree"          "epsilon"        
#>  [9] "fitted"          "gamma"           "kernel"          "nu"             
#> [13] "scale"           "shrinking"       "tolerance"       "type"