Representational primitives using trend based global features for time series classification

Feature based learning of time series sequences contains a systematic step of preprocessing, representing and analyzing the properties of time series elements. Representational features include the mapping of time series properties namely trend, seasonality and stationarity. Usually, the segmented g...

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Veröffentlicht in:	Expert systems with applications 2021-04, Vol.167, p.114376, Article 114376
Hauptverfasser:	C.I., Johnpaul, Prasad, Munaga V.N.K., Nickolas, S., Gangadharan, G.R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Classification Combined trendlet vector Datasets Decision trees Feature extraction Global features Machine learning Properties (attributes) Regression analysis Reversal points Sequences Time series
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