extractFDAFPCA: Extract functional principal component analysis features.

In berndbischl/mlr: Machine Learning in R

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()

berndbischl/mlr documentation built on Aug. 15, 2024, 4:20 p.m.