Papers › FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification
FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification
Joscha Diehl, Richard Krieg
We introduce a pipeline for time series classification that extracts features based on the iterated-sums signature (ISS) and then applies a linear classifier. These features are intrinsically nonlinear, capture chronological information, and, under certain settings, are invariant to time-warping. We are competitive with state-of-the-art methods on the UCR archive, both in terms of accuracy and speed. We make our code available at \url{https://github.com/irkri/fruits}.
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