calculate_features {theft} | R Documentation |
Compute features on an input time series dataset
Description
Compute features on an input time series dataset
Usage
calculate_features(
data,
feature_set = c("catch22", "feasts", "tsfeatures", "kats", "tsfresh", "tsfel"),
features = NULL,
catch24 = FALSE,
tsfresh_cleanup = FALSE,
use_compengine = FALSE,
seed = 123
)
Arguments
data |
tbl_ts containing the time series data
|
feature_set |
character or vector of character denoting the set of time-series features to calculate. Can be one of "catch22" , "feasts" , "tsfeatures" , "tsfresh" , "tsfel" , or "kats"
|
features |
named list containing a set of user-supplied functions to calculate on data . Each function should take a single argument which is the time series. Defaults to NULL for no manually-specified features. Each list entry must have a name as calculate_features looks for these to name the features. If you don't want to use the existing feature sets and only compute those passed to features , set feature_set = NULL
|
catch24 |
Boolean specifying whether to compute catch24 in addition to catch22 if catch22 is one of the feature sets selected. Defaults to FALSE
|
tsfresh_cleanup |
Boolean specifying whether to use the in-built tsfresh relevant feature filter or not. Defaults to FALSE
|
use_compengine |
Boolean specifying whether to use the "compengine" features in tsfeatures . Defaults to FALSE to provide immense computational efficiency benefits
|
seed |
integer denoting a fixed number for R's random number generator to ensure reproducibility. Defaults to 123
|
Value
object of class feature_calculations
that contains the summary statistics for each feature
Author(s)
Trent Henderson
Examples
featMat <- calculate_features(data = simData,
feature_set = "catch22")
[Package
theft version 0.8.1
Index]