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}.