mlr_learners_surv.dnn: Survival DNNSurv Learner

In mlr3learners/mlr3learners.proba: Learners for mlr3proba

Description

A mlr3proba::LearnerSurv implementing the DNNSurv neural network. Code for generating the conditional probabilities and pre-processing data is taken from https://github.com/lilizhaoUM/DNNSurv.

Dictionary

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

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

Super classes

mlr3::Learner -> mlr3proba::LearnerSurv -> LearnerSurvDNNSurv

Methods

Public methods

• LearnerSurvDNNSurv$new()

• LearnerSurvDNNSurv$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

LearnerSurvDNNSurv$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerSurvDNNSurv$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Zhao, L., & Feng, D. (2020). DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values. https://arxiv.org/abs/1908.02337

See Also

Dictionary of Learners: mlr3::mlr_learners

Examples

if (requireNamespace("mlr3learners.proba")) {
  learner = mlr3::lrn("surv.dnn")
  print(learner)

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

mlr3learners/mlr3learners.proba documentation built on Aug. 9, 2020, 12:50 a.m.