Linearly Transform the Domain of Functional Data

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()
#>       heatan    h20                        NIR                      UVVIS
#>        <num>  <num>                  <tfd_reg>                  <tfd_reg>
#>   1: 26.7810 2.3000 ▇▇▇█████████████████████▇▇ ▆▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇███████
#>   2: 27.4720 3.0000 ▆▇▇▇▇▇▇▇▇█████████████████ ▂▂▁▂▁▁▁▁▁▂▂▂▂▂▂▂▂▂▂▃▃▃▃▃▃▃
#>   3: 23.8400 2.0002 ▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅ ▄▃▃▃▃▃▃▃▃▃▃▃▃▄▄▄▄▄▄▄▄▄▄▄▄▄
#>   4: 18.1680 1.8500 ▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅ ▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▃▄▃▃
#>   5: 17.5170 2.3898 ▄▅▅▅▅▅▅▅▅▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆ ▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▃▃▃▃▃▃▃
#>  ---                                                                     
#> 125: 23.8340 2.1100 ▅▅▅▅▅▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆ ▃▃▃▃▃▃▃▃▃▃▂▂▃▃▃▃▃▃▃▃▃▃▃▃▃▃
#> 126: 11.8050 1.6200 ▂▂▂▂▃▃▃▃▃▃▃▄▄▄▄▄▄▄▄▅▅▅▅▅▅▆ ▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▂▂▂▂▂▂▂▂▂
#> 127:  8.8315 1.4200 ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▄▅▅▅▅▆ ▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▂▂▂▂
#> 128: 11.3450 1.4800 ▅▅▅▅▅▅▆▆▆▆▆▆▆▆▆▇▇▇▇▇▆▆▆▆▆▆ ▆▆▆▆▆▆▆▆▅▅▅▅▅▅▅▆▆▆▆▆▆▆▆▆▆▆
#> 129: 28.9940 2.5000 ▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆ ▂▂▂▂▂▂▂▂▂▂▂▂▃▃▃▃▃▃▃▃▃▃▃▃▃▃