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Linearly Transform the Domain of Functional Data

Source: R/PipeOpFDAScaleRange.R
mlr_pipeops_fda.scalerange.Rd

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

Inherited methods

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().

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
#>        <num>  <num>
#>   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
#>                                                                                         NIR
#>                                                                                   <tfd_reg>
#>   1:                   0.2340554,0.2904143,0.2985390,0.2857719,0.4317163,0.4128493,...[231]
#>   2:                   0.2438254,0.3175793,0.1569265,0.3040594,0.2788988,0.2041318,...[231]
#>   3:       -0.05197412, 0.04500882,-0.07834500, 0.12620942,-0.09833023, 0.02935566,...[231]
#>   4: -0.081765370,-0.082304927, 0.058605750,-0.024858584,-0.006321834,-0.060674486,...[231]
#>   5:       -0.22812462,-0.11606918,-0.04202395,-0.11545658,-0.08707948,-0.07724899,...[231]
#>  ---                                                                                       
#> 125: -0.036677545,-0.022985177,-0.061758800,-0.064472334, 0.003787266, 0.013341814,...[231]
#> 126:             -0.6298321,-0.5693807,-0.6526985,-0.5576706,-0.5950987,-0.5608432,...[231]
#> 127:             -0.7318596,-0.8153782,-0.8011885,-0.7131156,-0.7716812,-0.7441482,...[231]
#> 128:       -0.05811752,-0.04569275,-0.00528125,-0.02657358,-0.13537198,-0.07541799,...[231]
#> 129:             0.10433463,0.11665357,0.17538400,0.09664192,0.16000127,0.15103676,...[231]
#>                                                                                 UVVIS
#>                                                                             <tfd_reg>
#>   1:             0.8743160,0.7481823,0.7738064,0.7471426,0.5223545,0.8142814,...[134]
#>   2:       -0.8551739,-1.2873925,-0.8328261,-0.9758280,-0.7976276,-0.9203199,...[134]
#>   3: -0.08469889,-0.29369554,-0.20151308,-0.26229300,-0.27280263,-0.31936488,...[134]
#>   4:       -0.5821539,-0.4851725,-0.3282551,-0.5389530,-0.4092186,-0.3816549,...[134]
#>   5:       -0.6435039,-1.1232725,-0.6649561,-0.7912230,-0.7875426,-0.7048599,...[134]
#>  ---                                                                                 
#> 125:       -0.5410239,-0.6731825,-0.5898611,-0.4922130,-0.7685726,-0.4825299,...[134]
#> 126:       -0.9610539,-0.8193925,-1.0801311,-0.8345630,-0.8032476,-0.6774949,...[134]
#> 127:       -0.8867289,-0.6289675,-0.9939461,-0.6830530,-0.9279676,-0.7833399,...[134]
#> 128:             0.5159331,0.5713029,0.6108473,0.5342805,0.6325831,0.7383201,...[134]
#> 129:       -0.5392589,-1.3016675,-0.7902711,-0.7808930,-0.5305326,-0.7518349,...[134]