Hydra: competing convolutional kernels for fast and accurate time series classification

• Published in: Data mining and knowledge discovery Vol. 37; no. 5; pp. 1779 - 1805
• Main Authors: Dempster, Angus, Schmidt, Daniel F., Webb, Geoffrey I.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2023; Springer Nature B.V
• Subjects: Accuracy; Archives & records; Artificial Intelligence; Chemistry and Earth Sciences; Classification; Computer Science; Data Mining and Knowledge Discovery; Datasets; Dictionaries; Information Storage and Retrieval; Kernels; Methods; Physics; Statistics for Engineering; Time series; Dictionary; Convolution; Random; Rocket; Time series classification

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 adjus...