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Shapelet Discovery by Lazy Time Series Classification
Joint Authors
Zhang, Wei
Yuan, Jidong
Hao, Shilei
Wang, Zhihai
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-26
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
As a representation of discriminative features, the time series shapelet has recently received considerable research interest.
However, most shapelet-based classification models evaluate the differential ability of the shapelet on the whole training dataset, neglecting characteristic information contained in each instance to be classified and the classwise feature frequency information.
Hence, the computational complexity of feature extraction is high, and the interpretability is inadequate.
To this end, the efficiency of shapelet discovery is improved through a lazy strategy fusing global and local similarities.
In the prediction process, the strategy learns a specific evaluation dataset for each instance, and then the captured characteristics are directly used to progressively reduce the uncertainty of the predicted class label.
Moreover, a shapelet coverage score is defined to calculate the discriminability of each time stamp for different classes.
The experimental results show that the proposed method is competitive with the benchmark methods and provides insight into the discriminative features of each time series and each type in the data.
American Psychological Association (APA)
Zhang, Wei& Wang, Zhihai& Yuan, Jidong& Hao, Shilei. 2020. Shapelet Discovery by Lazy Time Series Classification. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1138717
Modern Language Association (MLA)
Zhang, Wei…[et al.]. Shapelet Discovery by Lazy Time Series Classification. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-19.
https://search.emarefa.net/detail/BIM-1138717
American Medical Association (AMA)
Zhang, Wei& Wang, Zhihai& Yuan, Jidong& Hao, Shilei. Shapelet Discovery by Lazy Time Series Classification. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1138717
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138717