The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances

In the last 5 years there have been a large number of new time series classification algorithms proposed in the literature. These algorithms have been evaluated on subsets of the 47 data sets in the University of California, Riverside time series classification archive. The archive has recently been expanded to 85 data sets, over half of which have been donated by researchers at the University of East Anglia. Aspects of previous evaluations have made comparisons between algorithms difficult. For example, several different programming languages have been used, experiments involved a single train/test split and some used normalised data whilst others did not. The relaunch of the archive provides a timely…

• UO
  University of East Anglia
• EA
  Engineering and Physical Sciences Research Council

  Awards: EP/M015807/1, EP/M015087/1