Smoclust: synthetic minority oversampling based on stream clustering for evolving data streams
(2023)
Journal Article
Chiu, C. W., & Minku, L. L. (2024). Smoclust: synthetic minority oversampling based on stream clustering for evolving data streams. Machine Learning, 113(7), 4671-4721. https://doi.org/10.1007/s10994-023-06420-y
Many real-world data stream applications not only suffer from concept drift but also class imbalance. Yet, very few existing studies investigated this joint challenge. Data difficulty factors, which have been shown to be key challenges in class imbal... Read More about Smoclust: synthetic minority oversampling based on stream clustering for evolving data streams.