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Moon et al., 2022 - Google Patents

An ensemble approach to anomaly detection using high-and low-variance principal components

Moon et al., 2022

Document ID
12185465999073697456
Author
Moon J
Yu J
Sohn K
Publication year
Publication venue
Computers and Electrical Engineering

External Links

Snippet

With the recent proliferation of cyber physical systems (CPSs), there is a growing demand for reliable anomaly detection systems. In this paper, we propose a new ensemble learning approach for anomaly detection that utilizes the extraction of specific features tailored to …
Continue reading at www.sciencedirect.com (other versions)

Classifications

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    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G06K9/6269—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches based on the distance between the decision surface and training patterns lying on the boundary of the class cluster, e.g. support vector machines
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