mlr_pipeops_fda.smooth {mlr3fda}R Documentation

Smoothing Functional Columns

Description

Smoothes functional data using tf::tf_smooth(). This preprocessing operator is similar to PipeOpFDAInterpol, however it does not interpolate to unobserved x-values, but rather smooths the observed values.

Parameters

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

Super classes

mlr3pipelines::PipeOp -> mlr3pipelines::PipeOpTaskPreproc -> mlr3pipelines::PipeOpTaskPreprocSimple -> PipeOpFDASmooth

Methods

Public methods

Inherited methods

Method new()

Initializes a new instance of this Class.

Usage
PipeOpFDASmooth$new(id = "fda.smooth", param_vals = list())
Arguments
id

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

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
PipeOpFDASmooth$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

task = tsk("fuel")
po_smooth = po("fda.smooth", method = "rollmean", args = list(k = 5))
task_smooth = po_smooth$train(list(task))[[1L]]
task_smooth
task_smooth$data(cols = c("NIR", "UVVIS"))

[Package mlr3fda version 0.2.0 Index]