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- W3119480724 abstract "The change of underlying data is one of the biggest challenges in non-stationary environments. While several algorithms have been proposed to detect these changes, substantial problems remain in the case of higher dimensional data. Thus, we propose a novel Concept Drift detector based on Minimum Enclosing Balls, with the capability to quickly process higher dimensional data. Additionally a kernelized version of this detector is derived, to process non-linear streaming data. We also propose a method to measure the performance of drift detectors with a binary classification evaluation technique, the confusion matrix, which enables calculating statistics like the F1 score. Our experiments show, that this novel technique is superior to existing state-of-the-art Concept Drift detectors regarding its true positive detection rate." @default.
- W3119480724 created "2021-01-18" @default.
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- W3119480724 date "2020-12-01" @default.
- W3119480724 modified "2023-10-14" @default.
- W3119480724 title "Reactive Concept Drift Detection Using Coresets Over Sliding Windows" @default.
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- W3119480724 doi "https://doi.org/10.1109/ssci47803.2020.9308521" @default.
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