Corpus ID: 21153674

A Shapelet Transform for Multivariate Time Series Classification

@article{Bostrom2017AST,
  title={A Shapelet Transform for Multivariate Time Series Classification},
  author={Aaron Bostrom and Anthony J. Bagnall},
  journal={ArXiv},
  year={2017},
  volume={abs/1712.06428}
}
  • Aaron Bostrom, Anthony J. Bagnall
  • Published 2017
  • Computer Science, Mathematics
  • ArXiv
  • Shapelets are phase independent subsequences designed for time series classification. We propose three adaptations to the Shapelet Transform (ST) to capture multivariate features in multivariate time series classification. We create a unified set of data to benchmark our work on, and compare with three other algorithms. We demonstrate that multivariate shapelets are not significantly worse than other state-of-the-art algorithms. 

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