Random Dilated Shapelet Transform: A New Approach for Time Series Shapelets

@inproceedings{Guillaume2022RandomDS,
  title={Random Dilated Shapelet Transform: A New Approach for Time Series Shapelets},
  author={Antoine Guillaume and Christel Vrain and Wael Elloumi},
  booktitle={ICPRAI},
  year={2022}
}
. Shapelet-based algorithms are widely used for time series classification because of their ease of interpretation, but they are currently outperformed by recent state-of-the-art approaches. We present a new formulation of time series shapelets including the notion of dilation, and we introduce a new shapelet feature to enhance their discriminative power for classification. Experiments performed on 112 datasets show that our method improves on the state-of-the-art shapelet algorithm, and achieves… 
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