R: Extract features from functional data.

extractFDAFeatures {mlr} | R Documentation

## Extract features from functional data.

### Description

Extract non-functional features from functional features using various methods. The function extractFDAFeatures performs the extraction for all functional features via the methods specified in `feat.methods` and transforms all mentioned functional matrix features into regular data.frame columns. Additionally, a “`extractFDAFeatDesc`” object which contains learned coefficients and other helpful data for extraction during the predict-phase is returned. This can be used with reextractFDAFeatures in order to extract features during the prediction phase.

### Usage

    extractFDAFeatures(obj, target = character(0L), feat.methods = list())

### Arguments

`obj` | (Task | data.frame) Task or data.frame to extract functional features from. Must contain functional features as matrix columns.
`target` | (character) Task target column. Only neccessary for data.frames Default is `character(0)`.
`feat.methods` | (named list) List of functional features along with the desired methods for each functional feature. “all” applies the extractFDAFeatures method to each functional feature. Names of `feat.methods` must match column names of functional features. Available feature extraction methods are available under family `fda_featextractor`. Default is list which does nothing.

### Details

The description object contains these slots

target character

  See argument.

coln character

  colum names of data.

fd.cols character

  Functional feature names.

extractFDAFeat list

  Contains `feature.methods` and relevant parameters for reextraction

.

### Value

(list)

`data (data.frame | Task)` | Extracted features, returns a data.frame when given a data.frame and a Task when given a Task.
`desc (`extractFDAFeatDesc`)` | Description object. See description for details.

### See Also

Other fda: `makeExtractFDAFeatMethod`, `makeExtractFDAFeatsWrapper`

[Package mlr version 2.13 Index]