Dynamic Time Warping Averaging of Time Series Allows Faster and More Accurate Classification

@article{Petitjean2014DynamicTW,
  title={Dynamic Time Warping Averaging of Time Series Allows Faster and More Accurate Classification},
  author={François Petitjean and Germain Forestier and Geoffrey I. Webb and Ann E. Nicholson and Yanping Chen and Eamonn J. Keogh},
  journal={2014 IEEE International Conference on Data Mining},
  year={2014},
  pages={470-479}
}
Recent years have seen significant progress in improving both the efficiency and effectiveness of time series classification. However, because the best solution is typically the Nearest Neighbor algorithm with the relatively expensive Dynamic Time Warping as the distance measure, successful deployments on resource constrained devices remain elusive. Moreover, the recent explosion of interest in wearable devices, which typically have limited computational resources, has created a growing need… CONTINUE READING

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