FRUITS: feature extraction using iterated sums for time series classification

Abstract 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 a form of time-warping. We achieve competitive results, both in accuracy and speed, on the UCR archive. We make our code available at https://github.com/irkri/fruits .