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

作者：

Highlights：

• 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.

摘要

•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.

论文关键词：Time series clustering,Dynamic time warping,Parametric distance measure

论文评审过程：Received 10 March 2016, Revised 23 May 2016, Accepted 8 June 2016, Available online 9 June 2016, Version of Record 18 June 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.06.012