mlr_learners_surv.deepsurv: Survival DeepSurv Learner

In mlr3learners/mlr3learners.pycox: Adds Learners from Python Package pycox for mlr3

Description

A mlr3proba::LearnerSurv implementing Deep-Surv from Python package https://pypi.org/project/pycox/.

Calls pycox.models.CoxPH.

Dictionary

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

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

Super classes

mlr3::Learner -> mlr3proba::LearnerSurv -> LearnerSurvDeepsurv

Methods

Public methods

• LearnerSurvDeepsurv$new()

• LearnerSurvDeepsurv$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

LearnerSurvDeepsurv$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerSurvDeepsurv$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Katzman, J. L., Shaham, U., Cloninger, A., Bates, J., Jiang, T., & Kluger, Y. (2018). DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network. BMC Medical Research Methodology, 18(1), 24. https://doi.org/10.1186/s12874-018-0482-1

See Also

Dictionary of Learners: mlr3::mlr_learners

Examples

if (requireNamespace("mlr3learners.pycox")) {
  learner = mlr3::lrn("surv.deepsurv")
  print(learner)

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

mlr3learners/mlr3learners.pycox documentation built on Sept. 24, 2020, 10:40 a.m.