Feature-based analyses of concept drift

Published: 2024, Last Modified: 11 Sept 2025Neurocomputing 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•Semantic modeling of relevant features for concept drift (explaining drift).•Algorithm-based modeling of relevant features (algorithmic improvement).•Efficient, adaptable, detector-agnostic solution to increase detection performance.•Theoretical analysis of relation of feature selection and drift detection.
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