R: Extract functional principal component analysis features.

extractFDAFPCA {mlr} | R Documentation

## Extract functional principal component analysis features.

### Description

The function extracts the functional principal components from a data.frame containing functional features. Uses `stats::prcomp`.

### Usage

    extractFDAFPCA(rank. = NULL, center = TRUE, scale. = FALSE)

### Arguments

`rank.` | (`integer(1)`) Number of principal components to extract. Default is `NULL`
`center` | (`logical(1)`) Should data be centered before applying PCA?
`scale.` | (`logical(1)`) Should data be scaled before applying PCA?

### Value

(data.frame).

### See Also

Other fda_featextractor: `extractFDABsignal()`, `extractFDADTWKernel()`, `extractFDAFourier()`, `extractFDAMultiResFeatures()`, `extractFDATsfeatures()`, `extractFDAWavelets()`

[Package mlr version 2.19.0 Index]