extractFDADTWKernel: DTW kernel features

In mlr: Machine Learning in R

DTW kernel features

Description

The function extracts features from functional data based on the DTW distance with a reference dataframe.

Usage

extractFDADTWKernel(
  ref.method = "random",
  n.refs = 0.05,
  refs = NULL,
  dtwwindow = 0.05
)

Arguments

ref.method	(character(1)) How should the reference curves be obtained? Method random draws n.refs random reference curves, while all uses all curves as references. In order to use user-provided reference curves, this parameter is set to fixed.
n.refs	(numeric(1)) Number of reference curves to be drawn (as a fraction of the number of observations in the training data).
refs	(matrix|integer(n)) Integer vector of training set row indices or a matrix of reference curves with the same length as the functionals in the training data. Overwrites ref.method and n.refs.
dtwwindow	(numeric(1)) Size of the warping window size (as a proportion of query length).

Value

(data.frame).

See Also

Other fda_featextractor: extractFDABsignal(), extractFDAFPCA(), extractFDAFourier(), extractFDAMultiResFeatures(), extractFDATsfeatures(), extractFDAWavelets()

mlr documentation built on June 22, 2024, 10:51 a.m.