Should we Reload Time Series Classification Performance Evaluation ? (a position paper)

Dominique Gay; Vincent Lemaire

Should we Reload Time Series Classification Performance Evaluation ? (a position paper)

Machine Learning 2019-03-11 v1 Machine Learning

Authors: Dominique Gay , Vincent Lemaire

Abstract

Since the introduction and the public availability of the \textsc{ucr} time series benchmark data sets, numerous Time Series Classification (TSC) methods has been designed, evaluated and compared to each others. We suggest a critical view of TSC performance evaluation protocols put in place in recent TSC literature. The main goal of this `position' paper is to stimulate discussion and reflexion about performance evaluation in TSC literature.

Cite

@article{arxiv.1903.03300,
  title  = {Should we Reload Time Series Classification Performance Evaluation ? (a position paper)},
  author = {Dominique Gay and Vincent Lemaire},
  journal= {arXiv preprint arXiv:1903.03300},
  year   = {2019}
}

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8 pages

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