mlr_learners_surv.svm: Survival Support Vector Machine Learner

In mlr3learners/mlr3learners.survivalsvm: Learners from the {survivalsvm} package for 'mlr3'

Description

A mlr3proba::LearnerSurv implementing svm from package survivalsvm. Calls survivalsvm::survivalsvm().

Details

Four possible SVMs can be implemented, dependent on the type parameter. These correspond to predicting the survival time via regression (regression), predicting a continuous rank (vanbelle1, vanbelle2), or a hybrid of the two (hybrid). Whichever type is chosen determines how the crank predict type is calculated, but in any case all can be considered a valid continuous ranking.

Dictionary

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

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

Super classes

mlr3::Learner -> mlr3proba::LearnerSurv -> LearnerSurvSVM

Methods

Public methods

• LearnerSurvSVM$new()

• LearnerSurvSVM$clone()

Inherited methods

• mlr3::Learner$format()

• mlr3::Learner$help()

• mlr3::Learner$predict()

• mlr3::Learner$predict_newdata()

• mlr3::Learner$print()

• mlr3::Learner$reset()

• mlr3::Learner$train()

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Method new()

Creates a new instance of this R6 class.

Usage

LearnerSurvSVM$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerSurvSVM$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Belle VV, Pelckmans K, Huffel SV, Suykens JAK (2010). “Improved performance on high-dimensional survival data by application of Survival-SVM.” Bioinformatics, 27(1), 87–94. doi: 10.1093/bioinformatics/btq617.

Belle VV, Pelckmans K, Huffel SV, Suykens JA (2011). “Support vector methods for survival analysis: a comparison between ranking and regression approaches." Artificial Intelligence in Medicine, 53(2), 107–118. doi: 10.1016/j.artmed.2011.06.006.

Shivaswamy, P. K., Chu, W., & Jansche, M. (2007). A support vector approach to censored targets. In Proceedings - IEEE International Conference on Data Mining, ICDM (pp. 655–660). https://doi.org/10.1109/ICDM.2007.93

See Also

Dictionary of Learners: mlr3::mlr_learners

Examples

if (requireNamespace("survivalsvm")) {
  learner = mlr3::lrn("surv.svm")
  print(learner)

  # available parameters:
  learner$param_set$ids()
}

mlr3learners/mlr3learners.survivalsvm documentation built on Aug. 2, 2020, 9:40 a.m.