A pattern dictionary method for anomaly detection

HIGHLIGHTS

• who: Elyas Sabeti et al. from the Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI, USA have published the Article: A Pattern Dictionary Method for Anomaly Detection, in the Journal: Entropy 2022, 24, 1095. of /2022/
• what: The authors propose a compression-based anomaly detection method for time series and sequence data using a pattern dictionary. While the proposed pattern dictionary can be used as a stand-alone anomaly detection method (Pattern Dictionary for Detection (PDD)), the authors show how it can be utilized in the atypicality framework for more general data . . .
  

   

  

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