When is Early Classification of Time Series Meaningful? (Extended Abstract)
Renjie Wu, Audrey Der, Eamonn Keogh · 2022 IEEE 38th International Conference on Data Engineering (ICDE) · 2022
The problem of early classification of time series (ETSC) generalizes classic time series classification to ask if we can classify a time series subsequence with sufficient accuracy and confidence after seeing only some prefix of a target pattern. The idea is that the earlier classification would allow us to take immediate actions, such as sounding an alarm or applying the brakes in an automobile. In this work, we make a surprising claim. In spite of the fact that there are dozens of papers on ETSC, it is not clear that any of them could ever work in a real-world setting. The issue is not with the algorithms per se, but with the vague and underspecified problem definition.