Extract non-functional features from functional features using various methods.
The function extractFDAFeatures performs the extraction for all functional features
via the methods specified in feat.methods and transforms all mentioned functional
matrix features into regular data.frame columns.
Additionally, a “extractFDAFeatDesc” object
which contains learned coefficients and other helpful data for
extraction during the predict-phase is returned. This can be used with
reextractFDAFeatures in order to extract features during the prediction phase.
extractFDAFeatures(obj, target = character(0L), feat.methods = list())(Task | data.frame) Task or data.frame to extract functional features from. Must contain functional features as matrix columns.
(character)
Task target column. Only neccessary for data.frames
Default is character(0).
(named list)
List of functional features along with the desired methods for each functional feature.
“all” applies the extractFDAFeatures method to each
functional feature.
Names of feat.methods must match column names of functional features.
Available feature extraction methods are available under family fda_featextractor.
Default is list which does nothing.
(list)
Extracted features, returns a data.frame when given a data.frame and a Task when given a Task.
extractFDAFeatDesc)Description object. See description for details.
The description object contains these slots
Other fda: makeExtractFDAFeatMethod,
makeExtractFDAFeatsWrapper