`R/LearnerSurvRandomForestSRC.R`

`LearnerSurvRandomForestSRC.Rd`

A LearnerSurv for a survival random forest implemented in `randomForestSRC::rfsrc()`

in package randomForestSRC.

`R6::R6Class()`

inheriting from LearnerSurv.

`rfsrc`

has three prediction outcomes, from the fitted model these are
respectively:

predicted - This is ensemble mortality defined in Ishwaran et al. (2008), the sum of an individuals cumulative hazard function over all time-points

chf - Cumulative hazard function, estimated via a bootstrapped Nelson-Aalen estimator (Ishwaran, 2008)

surv - Survival function, estimated via a bootrstrapped Kaplan-Meier estimate (https://kogalur.github.io/randomForestSRC/theory.html)

Only the second two of these are returned in the `distr`

predict.type, as Nelson-Aalen and Kaplan-Meier
will give different results, the estimator can be chosen in the parameter set under "estimator".

The 'risk' predict.type is here defined as the mean of the cumulative hazard over all unique death times.

LearnerSurvRandomForestSRC$new() mlr_learners$get("surv.randomForestSRC") lrn("surv.randomForestSRC")

Ishwaran H. and Kogalur U.B. (2019). Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC), R package version 2.9.1.

Ishwaran H., Kogalur U.B., Blackstone E.H. and Lauer M.S. (2008). Random survival forests. Ann. Appl. Statist. 2(3), 841--860.

Breiman, L. (2001). Random Forests. Machine Learning 45(1). doi: 10.1023/A:1010933404324 .