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HYDRA: Competing convolutional kernels for fast and accurate time series classification. (arXiv:2203.13652v1 [cs.LG])
March 28, 2022, 1:11 a.m. | Angus Dempster, Daniel F. Schmidt, Geoffrey I. Webb
cs.LG updates on arXiv.org arxiv.org
We demonstrate a simple connection between dictionary methods for time series
classification, which involve extracting and counting symbolic patterns in time
series, and methods based on transforming input time series using convolutional
kernels, namely ROCKET and its variants. We show that by adjusting a single
hyperparameter it is possible to move by degrees between models resembling
dictionary methods and models resembling ROCKET. We present HYDRA, a simple,
fast, and accurate dictionary method for time series classification using
competing convolutional kernels, …
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