LGApr 27, 2021

Early Classification of Time Series is Meaningful

arXiv:2104.13257v24 citations
Originality Synthesis-oriented
AI Analysis

It defends the relevance of early classification for applications like healthcare and finance, but is incremental as it primarily rebuts existing claims.

The paper addresses criticisms that early classification of time series research is flawed by responding to issues raised in a preprint and proposing new application directions.

Many approaches have been proposed for early classification of time series in light of its significance in a wide range of applications including healthcare, transportation and finance. However, recently a preprint saved on Arxiv claim that all research done for almost 20 years now on the Early Classification of Time Series is useless, or, at the very least, ill-oriented because severely lacking a strong ground. In this paper, we answer in detail the main issues and misunderstandings raised by the authors of the preprint, and propose directions to further expand the fields of application of early classification of time series.

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