Adaptive cost dynamic time warping distance in time series analysis for classification
作者：
Highlights：
• Adaptive cost is introduced to dynamic time warping for better classification.
• Cost function is proposed for dynamic time warping.
• Experiments on UCR datasets prove that AC-DTW perform better than other methods.
摘要
•Adaptive cost is introduced to dynamic time warping for better classification.•Cost function is proposed for dynamic time warping.•Experiments on UCR datasets prove that AC-DTW perform better than other methods.
论文关键词：Time series classification,Dynamic time warping,Adaptive cost,Nearest neighbor classifier
论文评审过程：Received 4 September 2016, Revised 20 October 2016, Available online 25 January 2017, Version of Record 16 February 2017.
论文官网地址：https://doi.org/10.1016/j.cam.2017.01.004
