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

Gay, Dominique, Lemaire, Vincent

arXiv.org Machine Learning 

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.

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