SCALE-BOSS: A framework for scalable time-series classification using symbolic representations

Author:

Glenis Apostolos1,Vouros George A.1

Affiliation:

1. Department of Digital Systems, University of Piraeus, Greece

Publisher

ACM

Reference27 articles.

1. Albert Bifet , Geoff Holmes , Bernhard Pfahringer , Philipp Kranen , Hardy Kremer , Timm Jansen , and Thomas Seidl . 2010 . Moa: Massive online analysis, a framework for stream classification and clustering . In Proceedings of the first workshop on applications of pattern analysis. PMLR, 44–50 . Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, and Thomas Seidl. 2010. Moa: Massive online analysis, a framework for stream classification and clustering. In Proceedings of the first workshop on applications of pattern analysis. PMLR, 44–50.

2. Aaron Bostrom and Anthony Bagnall . 2017. Binary shapelet transform for multiclass time series classification . In Transactions on Large-Scale Data-and Knowledge-Centered Systems XXXII. Springer , 24–46. Aaron Bostrom and Anthony Bagnall. 2017. Binary shapelet transform for multiclass time series classification. In Transactions on Large-Scale Data-and Knowledge-Centered Systems XXXII. Springer, 24–46.

3. The UCR time series archive

4. ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels

5. MiniRocket

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