Ranking by Aggregating Referees: Evaluating the Informativeness of Explanation Methods for Time Series Classification

Author:

Agarwal Surabhi,Nguyen Trang Thu,Nguyen Thach Le,Ifrim Georgiana

Publisher

Springer International Publishing

Reference26 articles.

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2. Bagnall, A., Flynn, M., Large, J., Lines, J., Middlehurst, M.: A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0 (2020). http://arxiv.org/abs/2004.06069

3. Bagnall, A., Lines, J., Bostrom, A., Large, J., Keogh, E.: The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Min. Knowl. Disc. 31(3), 606–660 (2016). https://doi.org/10.1007/s10618-016-0483-9

4. Dempster, A., Petitjean, F., Webb, G.I.: ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels. DAMI. https://link.springer.com/article/10.1007/s10618-020-00701-z

5. Deng, H., Runger, G., Tuv, E., Vladimir, M.: A time series forest for classification and feature extraction. Inf. Sci. 239, 142–153 (2013)

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