2023
DOI: 10.1109/access.2023.3252004
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Dynamic Construction of Outlier Detector Ensembles With Bisecting K-Means Clustering

Abstract: Outlier detection (OD) is a key problem, for which numerous solutions have been proposed. To deal with the difficulties associated with outlier detection across various domains and data characteristics, ensembles of outlier detectors have recently been employed to improve the performance of individual outlier detectors. In this paper, we follow an ensemble outlier detection approach in which good outlier detectors are selected through an enhanced clustering-based dynamic selection (CBDS) method. In this method… Show more

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Cited by 3 publications
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References 61 publications
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