mlr3fda (version 0.2.0)

mlr_pipeops_fda.scalerange: Linearly Transform the Domain of Functional Data.

Description

Linearly transform the domain of functional data so they are between lower and upper. The formula for this is \(x' = offset + x * scale\), where \(scale\) is \((upper - lower) / (max(x) - min(x))\) and \(offset\) is \(-min(x) * scale + lower\). The same transformation is applied during training and prediction.

Parameters

The parameters are the parameters inherited from PipeOpTaskPreproc, as well as the following parameters:

• lower :: numeric(1)
  Target value of smallest item of input data. Initialized to 0.

• uppper :: numeric(1)
  Target value of greatest item of input data. Initialized to 1.

Super classes

mlr3pipelines::PipeOp -> mlr3pipelines::PipeOpTaskPreproc -> PipeOpFDAScaleRange

Methods

Public methods

• PipeOpFDAScaleRange$new()

• PipeOpFDAScaleRange$clone()

Inherited methods

• mlr3pipelines::PipeOp$help()
• mlr3pipelines::PipeOp$predict()
• mlr3pipelines::PipeOp$print()
• mlr3pipelines::PipeOp$train()

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Method new()

Initializes a new instance of this Class.

Usage

PipeOpFDAScaleRange$new(id = "fda.scalerange", param_vals = list())

Arguments

id

(character(1))
Identifier of resulting object, default "fda.scalerange".

param_vals

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

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Method clone()

The objects of this class are cloneable with this method.

Usage

PipeOpFDAScaleRange$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

task = tsk("fuel")
po_scale = po("fda.scalerange", lower = -1, upper = 1)
task_scale = po_scale$train(list(task))[[1L]]
task_scale$data()