mlr_pipeops_trafopred_survregr: PipeOpPredSurvRegr

In mlr3proba: Probabilistic Supervised Learning for 'mlr3'

PipeOpPredSurvRegr

Description

Transform PredictionSurv to PredictionRegr.

Input and Output Channels

Input and output channels are inherited from PipeOpPredTransformer.

The output is the input PredictionSurv transformed to a PredictionRegr. Censoring is ignored. crank and lp predictions are also ignored.

State

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

Super classes

mlr3pipelines::PipeOp -> mlr3proba::PipeOpTransformer -> mlr3proba::PipeOpPredTransformer -> PipeOpPredSurvRegr

Methods

Public methods

• PipeOpPredSurvRegr$new()

• PipeOpPredSurvRegr$clone()

Inherited methods

• mlr3pipelines::PipeOp$predict()

• mlr3pipelines::PipeOp$print()

• mlr3pipelines::PipeOp$train()

---

Method new()

Creates a new instance of this R6 class.

Usage

PipeOpPredSurvRegr$new(id = "trafopred_survregr")

Arguments

id

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

---

Method clone()

The objects of this class are cloneable with this method.

Usage

PipeOpPredSurvRegr$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_trafotask_regrsurv, mlr_pipeops_trafotask_survregr

Other Transformation PipeOps: mlr_pipeops_trafopred_regrsurv, mlr_pipeops_trafotask_regrsurv, mlr_pipeops_trafotask_survregr

Examples

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

  # simple example
  pred = PredictionSurv$new(row_ids = 1:10, truth = Surv(1:10, rbinom(10, 1, 0.5)),
    response = 1:10)
  po = po("trafopred_survregr")
  new_pred = po$predict(list(pred = pred))[[1]]
  print(new_pred)
}

## End(Not run)

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