TEASER: early and accurate time series classification

• Published in: Data mining and knowledge discovery Vol. 34; no. 5; pp. 1336 - 1362
• Main Authors: Schäfer, Patrick, Leser, Ulf
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2020; Springer Nature B.V
• Subjects: Accuracy; Algorithms; Artificial Intelligence; Chemistry and Earth Sciences; Classification; Classifiers; Computer Science; Data Mining and Knowledge Discovery; Data points; Gait; Gait recognition; Information Storage and Retrieval; Journal Track of ECML PKDD 2020; Physics; Statistics for Engineering; Time series; Early classification; Framework; Time series; Accurate

Early time series classification (eTSC) is the problem of classifying a time series after as few measurements as possible with the highest possible accuracy. The most critical issue of any eTSC method is to decide when enough data of a time series has been seen to take a decision: Waiting for more d...