Generates plots for mlr3proba::PredictionSurv, depending on argument type:

  • "calib" (default): Calibration plot comparing the average predicted survival distribution to a Kaplan-Meier prediction, this is not a comparison of a stratified crank or lp prediction. object must have distr prediction. geom_line() is used for comparison split between the prediction (Pred) and Kaplan-Meier estimate (KM). In addition labels are added for the x (T) and y (S(T)) axes.

# S3 method for PredictionSurv
autoplot(
  object,
  type = "calib",
  task = NULL,
  row_ids = NULL,
  times = NULL,
  ...
)

Arguments

object

(mlr3proba::PredictionSurv).

type

(character(1)):
Type of the plot. See description.

task

(mlr3proba::TaskSurv)
If type = "calib" then task is passed to $predict in the Kaplan-Meier learner.

row_ids

(integer())
If type = "calib" then row_ids is passed to $predict in the Kaplan-Meier learner.

times

(numeric())
If type = "calib" then times is the values on the x-axis to plot over, if NULL uses all times from task.

...

(any): Additional arguments, currently unused.

Examples

library(mlr3) library(mlr3proba) library(mlr3viz) learn = lrn("surv.coxph") task = tsk("rats") p = learn$train(task, row_ids = 1:100)$predict(task, row_ids = 101:200)
#> Warning: Loglik converged before variable 3 ; coefficient may be infinite.
autoplot(p, type = "calib", task = task)