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Implement KShape anomaly detector [1], which detects anomalies by measuring the distance from multiple normal behaviors. These normal behaviors are identified using KShape clustering.
[1] J. Paparrizos and L. Gravano. k-shape: Efficient and accurate clustering of time series. In Proceedings of the 2015 ACM SIGMOD international conference on management of data, pages 1855–1870, 2015.
The text was updated successfully, but these errors were encountered:
Implement KShape anomaly detector [1], which detects anomalies by measuring the distance from multiple normal behaviors. These normal behaviors are identified using KShape clustering.
[1] J. Paparrizos and L. Gravano. k-shape: Efficient and accurate clustering of time series. In Proceedings of the 2015 ACM SIGMOD international conference on management of data, pages 1855–1870, 2015.
The text was updated successfully, but these errors were encountered: