mlr3fda (version 0.2.0)

mlr_pipeops_fda.smooth: 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:

• method :: character(1)
  One of:

  • "lowess": locally weighted scatterplot smoothing (default)

  • "rollmean": rolling mean

  • "rollmedian": rolling meadian

  • "savgol": Savitzky-Golay filtering

  All methods but "lowess" ignore non-equidistant arg values.

• args :: named list()
  List of named arguments that is passed to tf_smooth(). See the help page of tf_smooth() for default values.

• verbose :: logical(1)
  Whether to print messages during the transformation. Is initialized to FALSE.

Super classes

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

Methods

Public methods

• PipeOpFDASmooth$new()

• PipeOpFDASmooth$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

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().

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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"))