2020
DOI: 10.1007/s11042-020-09366-8
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Early classification of multivariate data by learning optimal decision rules

Abstract: Early classification on time series has emerged as an active research area in the field of machine learning. It covers a wide range of applications in agriculture, medical and multimedia systems, including drought prediction, health monitoring, event detection, and many more. The early classification aims to predict the class label of a time series as soon as possible without waiting for the complete series. A critical issue in early classification is the learning of decision policy that determines the adequac… Show more

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Cited by 3 publications
(1 citation statement)
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“…Among them, the traditional methods leveraged hand-crafted features to train multiple classifiers, and set exiting strategies to quit classification. According to different exiting strategies [ 15 ], these methods can be divided into Prefix based [ 23 , 24 , 25 , 26 ], Shapelet based [ 27 , 28 , 29 , 30 ], and Model based [ 31 , 32 , 33 , 34 , 35 , 36 ] categories. Although these methods have achieved impressive performance and obtained extensive research, it is difficult to obtain the expert knowledge for constructing hand-crafted features as well as multiple classifiers.…”
Section: Related Workmentioning
confidence: 99%
“…Among them, the traditional methods leveraged hand-crafted features to train multiple classifiers, and set exiting strategies to quit classification. According to different exiting strategies [ 15 ], these methods can be divided into Prefix based [ 23 , 24 , 25 , 26 ], Shapelet based [ 27 , 28 , 29 , 30 ], and Model based [ 31 , 32 , 33 , 34 , 35 , 36 ] categories. Although these methods have achieved impressive performance and obtained extensive research, it is difficult to obtain the expert knowledge for constructing hand-crafted features as well as multiple classifiers.…”
Section: Related Workmentioning
confidence: 99%