Hierarchical clustering of time series data with parametric derivative dynamic time warping

•Combination of DTW and DDTW applied in a method of time series clustering.•Specific correction algorithm for the internal cluster validation measures.•Parameter selection for any dataset, giving the best clustering performance. Dynamic Time Warping (DTW) is a popular and efficient distance measure...

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Veröffentlicht in:	Expert systems with applications Jg. 62; S. 116 - 130
1. Verfasser:	Luczak, Maciej
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.11.2016
Schlagworte:	Algorithms Classification Clustering Derivatives Dynamic time warping Mathematical analysis Mathematical models Parametric distance measure Time series Time series clustering Warping Time series clustering Dynamic time warping Parametric distance measure
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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