PipeOpSimulateMissings {NADIA}R Documentation

PipeOpSimulateMissings

Description

Generates MCAR missing values in mlr3 pipeline according to set parameters. Missings are inserted to task data once during first training.

Input and Output Channels

Input and output channels are inherited from PipeOpTaskPreproc.

Parameters

Super classes

mlr3pipelines::PipeOp -> mlr3pipelines::PipeOpTaskPreproc -> PipeOpSimulateMissings

Methods

Public methods

Inherited methods

Method new()

Usage
PipeOpSimulateMissings$new(
  id = "simulate_missings",
  param_vals = list(per_missings = 50)
)

Method clone()

The objects of this class are cloneable with this method.

Usage
PipeOpSimulateMissings$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

{
  task_NA <- PipeOpSimulateMissings$new()$train(list(tsk("iris")))[[1]]

  # check
  sum(task_NA$missings()) > 0
}

[Package NADIA version 0.4.2 Index]