R: DTW kernel features

extractFDADTWKernel {mlr} | R Documentation

## 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()`

[Package mlr version 2.19.0 Index]