mlr_pipeops_trafotask_regrsurv: PipeOpTaskRegrSurv

In mlr3proba: Probabilistic Supervised Learning for 'mlr3'

PipeOpTaskRegrSurv

Description

Transform TaskRegr to TaskSurv.

Input and Output Channels

Input and output channels are inherited from PipeOpTaskTransformer.

The output is the input TaskRegr transformed to a TaskSurv.

State

The $state is a named list with the $state elements inherited from PipeOpTaskTransformer.

Parameters

The parameters are

• status :: (numeric(1))
  If NULL then assumed no censoring in the dataset. Otherwise should be a vector of 0/1s of same length as the prediction object, where 1 is dead and 0 censored.

Super classes

mlr3pipelines::PipeOp -> mlr3proba::PipeOpTransformer -> mlr3proba::PipeOpTaskTransformer -> PipeOpTaskRegrSurv

Methods

Public methods

• PipeOpTaskRegrSurv$new()

• PipeOpTaskRegrSurv$clone()

Inherited methods

• mlr3pipelines::PipeOp$predict()

• mlr3pipelines::PipeOp$print()

• mlr3pipelines::PipeOp$train()

---

Method new()

Creates a new instance of this R6 class.

Usage

PipeOpTaskRegrSurv$new(id = "trafotask_regrsurv")

Arguments

id

(character(1))
Identifier of the resulting object.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

PipeOpTaskRegrSurv$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Other PipeOps: PipeOpPredTransformer, PipeOpTaskTransformer, PipeOpTransformer, mlr_pipeops_survavg, mlr_pipeops_trafopred_regrsurv, mlr_pipeops_trafopred_survregr, mlr_pipeops_trafotask_survregr

Other Transformation PipeOps: mlr_pipeops_trafopred_regrsurv, mlr_pipeops_trafopred_survregr, mlr_pipeops_trafotask_survregr

Examples

## Not run: 
if (requireNamespace("mlr3pipelines", quietly = TRUE)) {
  library(mlr3)
  library(mlr3pipelines)

  task = tsk("boston_housing")
  po = po("trafotask_regrsurv")

  # assume no censoring
  new_task = po$train(list(task_regr = task, task_surv = NULL))[[1]]
  print(new_task)

  # add censoring
  task_surv = tsk("rats")
  task_regr = po("trafotask_survregr", method = "omit")$train(list(task_surv, NULL))[[1]]
  print(task_regr)
  new_task = po$train(list(task_regr = task_regr, task_surv = task_surv))[[1]]
  new_task$truth()
  task_surv$truth()
}

## End(Not run)

mlr3proba documentation built on April 25, 2022, 5:07 p.m.