Generalized linear models with elastic net regularization. Calls penalized::penalized() from package penalized.

Format

R6::R6Class() inheriting from LearnerSurv.

Construction

LearnerSurvPenalized$new()
mlr_learners$get("surv.penalized")
lrn("surv.penalized")

References

Goeman, J. J., L1 penalized estimation in the Cox proportional hazards model. Biometrical Journal 52(1), 7084.

See also

Examples

library(mlr3) task = tgen("simsurv")$generate(200) learner = lrn("surv.penalized") resampling = rsmp("cv", folds = 3) resample(task, learner, resampling)
#> <ResampleResult> of 3 iterations #> * Task: simsurv #> * Learner: surv.penalized #> * Performance: 0.535 [surv.harrells_c] #> * Warnings: 0 in 0 iterations #> * Errors: 0 in 0 iterations