Accelerating the discovery of unsupervised-shapelets

@article{Zakaria2015AcceleratingTD,
  title={Accelerating the discovery of unsupervised-shapelets},
  author={Jesin Zakaria and Abdullah Mueen and Eamonn J. Keogh and Neal E. Young},
  journal={Data Mining and Knowledge Discovery},
  year={2015},
  volume={30},
  pages={243-281}
}
Over the past decade, time series clustering has become an increasingly important research topic in data mining community. Most existing methods for time series clustering rely on distances calculated from the entire raw data using the Euclidean distance or Dynamic Time Warping distance as the distance measure. However, the presence of significant noise, dropouts, or extraneous data can greatly limit the accuracy of clustering in this domain. Moreover, for most real world problems, we cannot… CONTINUE READING

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