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Detecting anomalies in high-dimensional IoT data using hierarchical decomposition and one-class learning
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Detecting anomalies in high-dimensional IoT data using hierarchical decomposition and one-class learning

Volodymyr Koliadin Volodymyr Koliadin
Jul 21, 2022 • 46 min read

IntroductionAutomated health monitoring, including anomaly/fault detection, is an absolutely necessary attribute of any modern industrial system. Problems of this sort are usually solved through algorithmic processing of data from a great number of physical sensors installed in various equipment. A broad range of ML-based and statistical techniques are used...

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