Constructor for FDA feature extraction methods.

This can be used to implement custom feature FDA extraction.

makeExtractFDAFeatMethod(learn, reextract, args = list())

Arguments

learn

learn	(`function(data, target, col, ...)`) Function to learn and extract information on functional column `col`. Arguments are: data data.frame Data.frame with one row per observation of a single functional feature or time series and one column per measurement time point. All entries need to be numeric. data data.frame Data.frame containing matricies with one row per observation of a single functional or time series and one column per measurement time point. All entries need to be numeric. target character Name of the target variable. Default: “NULL”. The variable is only set to be consistent with the API. col (character \| numeric) column names or indices, the extraction should be performed on. The function has to return a named list of values.
reextract	(`function(data, target, col, ...)`) Function used for reextracting data in predict phase. Can be equal to `learn`.
args	(list) Named list of arguments to pass to `learn` via `...`.

(function(data, target, col, ...))
Function to learn and extract information on functional column col. Arguments are:

data data.frame
Data.frame with one row per observation of a single functional feature or time series and one column per measurement time point. All entries need to be numeric.
data data.frame
Data.frame containing matricies with one row per observation of a single functional or time series and one column per measurement time point. All entries need to be numeric.
target character
Name of the target variable. Default: “NULL”. The variable is only set to be consistent with the API.
col (character | numeric)
column names or indices, the extraction should be performed on. The function has to return a named list of values.

reextract

(function(data, target, col, ...))
Function used for reextracting data in predict phase. Can be equal to learn.

args

(list)
Named list of arguments to pass to learn via ....