Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms

Sina Däubener, Sebastian Schmitt, Hao Wang 0025, Peter Krause, Thomas Bäck. Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms. In Petra Perner, editor, Advances in Data Mining - Applications and Theoretical Aspects, 19th Industrial Conference, ICDM 2019, New York, USA, July 17 - July 21, 2019. pages 161-175, ibai publishing, 2019.

Abstract

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