PipeOpmissForest {NADIA}R Documentation

PipeOpmissForest

Description

Implements missForest methods as mlr3 pipeline more about missForest autotune_missForest

Input and Output Channels

Input and output channels are inherited from PipeOpImpute.

Parameters

The parameters include inherited from ['PipeOpImpute'], as well as:

Super classes

mlr3pipelines::PipeOp -> mlr3pipelines::PipeOpImpute -> missForest_imputation

Methods

Public methods

Inherited methods

Method new()

Usage
PipeOpmissForest$new(
  id = "impute_missForest_B",
  cores = NULL,
  ntree_set = c(100, 200, 500, 1000),
  mtry_set = NULL,
  parallel = FALSE,
  mtry = NULL,
  ntree = 100,
  optimize = FALSE,
  maxiter = 20,
  maxnodes = NULL,
  out_file = NULL
)

Method clone()

The objects of this class are cloneable with this method.

Usage
PipeOpmissForest$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples



  # Using debug learner for example purpose

  graph <- PipeOpmissForest$new() %>>% LearnerClassifDebug$new()
  graph_learner <- GraphLearner$new(graph)

  # Task with NA

  resample(tsk("pima"), graph_learner, rsmp("cv", folds = 3))


[Package NADIA version 0.4.2 Index]