PipeOpTaskTransformer: PipeOpTaskTransformer

In mlr3proba: Probabilistic Supervised Learning for 'mlr3'

PipeOpTaskTransformer

Description

Parent class for PipeOps that transform task objects top different types.

Input and Output Channels

PipeOpTaskTransformer has one input and output channel named "input" and "output". In training and testing these expect and produce mlr3::Task objects with the type depending on the transformers.

State

The $state is left empty (list()).

Internals

The commonality of methods using PipeOpTaskTransformer is that they take a mlr3::Task of one class and transform it to another class. This usually involves transformation of the data, which can be controlled via parameters.

Super classes

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

Methods

Public methods

• PipeOpTaskTransformer$new()

• PipeOpTaskTransformer$clone()

Inherited methods

• mlr3pipelines::PipeOp$predict()

• mlr3pipelines::PipeOp$print()

• mlr3pipelines::PipeOp$train()

---

Method new()

Creates a new instance of this R6 class.

Usage

PipeOpTaskTransformer$new(
  id,
  param_set = ps(),
  param_vals = list(),
  packages = character(0),
  input,
  output
)

Arguments

id

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

param_set

(paradox::ParamSet)
Set of hyperparameters.

param_vals

(list())
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise be set during construction.

packages

(character())
Set of required packages. A warning is signaled by the constructor if at least one of the packages is not installed, but loaded (not attached) later on-demand via requireNamespace().

input

data.table::data.table
data.table with columns name (character), train (character), predict (character). Sets the $input slot, see PipeOp.

output

data.table::data.table
data.table with columns name (character), train (character), predict (character). Sets the $output slot, see PipeOp.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

PipeOpTaskTransformer$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

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

Other Transformers: PipeOpPredTransformer, PipeOpTransformer

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