repr_feacliptrend: FeaClipTrend representation of time series
Description
The repr_feacliptrend computes representation of time series
based on feature extraction from bit-level representations (clipping and trending).
Usage
repr_feacliptrend(x, func, pieces = 2L, order = 4L)
Arguments
x
the numeric vector (time series)
func
the aggregation function for FeaTrend procedure (sumC or maxC)
pieces
the number of parts of time series to split
order
the order of simple moving average
Value
the numeric vector of frequencies of features
Details
FeaClipTrend combines FeaClip and FeaTrend representation methods.
See documentation of these two methods (check See Also section).
References
Laurinec P, and Lucka M (2018)
Interpretable multiple data streams clustering with clipped streams representation for the improvement of electricity consumption forecasting.
Data Mining and Knowledge Discovery. Springer. DOI: 10.1007/s10618-018-0598-2