We propose Expert Monitoring, an approach that leverages domain expertise to enhance the detection and mitigation of concept drift in machine learning (ML) models. Our approach supports practitioners by consolidating domain expertise related to concept drift-inducing events, making this expertise accessible to on-call personnel, and enabling automatic adaptability with expert oversight.
Leest, J., Raibulet, C., Gerostathopoulos, I., Lago, P. (2024). Expert Monitoring: Human-Centered Concept Drift Detection in Machine Learning Operations. In ICSE-NIER'24: Proceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results (pp.1-5). IEEE Computer Society [10.1145/3639476.3639771].
Expert Monitoring: Human-Centered Concept Drift Detection in Machine Learning Operations
Raibulet C.
;
2024
Abstract
We propose Expert Monitoring, an approach that leverages domain expertise to enhance the detection and mitigation of concept drift in machine learning (ML) models. Our approach supports practitioners by consolidating domain expertise related to concept drift-inducing events, making this expertise accessible to on-call personnel, and enabling automatic adaptability with expert oversight.
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Raibulet-ICSE_NIER-2024-VoR.pdf
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