Derivatives of Functional Columns — mlr_pipeops

Computes derivatives of functional features via tf::tf_derive(). For tfd inputs derivatives are obtained by finite differencing of the function evaluations, for tfb inputs by finite differencing of the basis functions.

Parameters

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

order :: integer(1)
Order of the derivative. Must be a positive integer. Initial value is 1.
arg :: numeric()
Optional grid to use for the finite differences. If NULL (the default), the argument grid of each functional column is used. For tfd_irreg inputs, supplying arg interpolates the data to a common grid before differentiating.

Super classes

mlr3pipelines::PipeOp -> mlr3pipelines::PipeOpTaskPreproc -> mlr3pipelines::PipeOpTaskPreprocSimple -> PipeOpFDADerive

Methods

Inherited methods

`PipeOpFDADerive$new()`

Initializes a new instance of this Class.

Usage

PipeOpFDADerive$new(id = "fda.derive", param_vals = list())

Arguments

id: (character(1))
Identifier of resulting object, default "fda.derive".
param_vals: (named list())
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise be set during construction. Default list().

`PipeOpFDADerive$clone()`

The objects of this class are cloneable with this method.

Usage

PipeOpFDADerive$clone(deep = FALSE)

Arguments

deep: Whether to make a deep clone.

Examples

task = tsk("fuel")
po_deriv = po("fda.derive", order = 1)
task_deriv = po_deriv$train(list(task))[[1L]]
task_deriv$data(cols = c("NIR", "UVVIS"))
#>                                                                                               NIR
#>                                                                                         <tfd_reg>
#>   1:        0.080476076, 0.032241810,-0.002321203, 0.066588633, 0.063538674,-0.056916652,...[231]
#>   2:        0.190957326,-0.043449440,-0.006759953, 0.060986133,-0.049963826, 0.003054598,...[231]
#>   3:        0.207151326,-0.013185440, 0.040600297,-0.009992617,-0.048426876, 0.073956348,...[231]
#>   4:             -0.07126467, 0.07018556, 0.02872317,-0.03246379,-0.01790795, 0.01027730,...[231]
#>   5:  0.1310605511, 0.0930503349, 0.0003062967,-0.0225277670, 0.0191037986,-0.0252437770,...[231]
#>  ---                                                                                             
#> 125:              0.03992536,-0.01254063,-0.02074358, 0.03277303, 0.03890707,-0.04242225,...[231]
#> 126:        0.132336076,-0.011433190, 0.005855047, 0.028799883,-0.001586326,-0.019654152,...[231]
#> 127:             -0.13237267,-0.03466444, 0.05113130, 0.01475363,-0.01551633, 0.03351710,...[231]
#> 128:       -0.001568599, 0.026418135, 0.009559584,-0.065045367,-0.024422201, 0.037028598,...[231]
#> 129:       -0.010886799, 0.035524685,-0.010005828,-0.007691367, 0.027197424,-0.003885402,...[231]
#>                                                                                       UVVIS
#>                                                                                   <tfd_reg>
#>   1:       -0.20201260,-0.05025479,-0.00051985,-0.12572598, 0.03356941, 0.15388724,...[134]
#>   2:       -0.87561120, 0.01117391, 0.15578227, 0.01759922, 0.02775406,-0.11878041,...[134]
#>   3:       -0.35958620,-0.05840709, 0.01570127,-0.03564478,-0.02853594,-0.05885541,...[134]
#>   4:        0.06701330, 0.12694941,-0.02689023,-0.04048178, 0.07864906,-0.03973241,...[134]
#>   5:       -0.94881120,-0.01072609, 0.16602477,-0.06129328, 0.04318156,-0.05838041,...[134]
#>  ---                                                                                       
#> 125: -0.239898704,-0.024418592, 0.090484772,-0.089355776, 0.004841559, 0.116339585,...[134]
#> 126:  0.342861296,-0.059538592,-0.007585228, 0.138441724, 0.078534059, 0.029389585,...[134]
#> 127:        0.56913130,-0.05360859,-0.02704273, 0.03298922,-0.05014344, 0.08097209,...[134]
#> 128:        0.06328260, 0.04745711,-0.01851120, 0.01086792, 0.10201979,-0.03862279,...[134]
#> 129:       -1.39931120,-0.12550609, 0.26038727, 0.12986922, 0.01452906,-0.18094041,...[134]