Characterizing Concept Drift
Data Min. Knowl. Discov., Volume abs/1511.03816, Issue 4, 2016.
Concept driftLearning from non-stationary distributionsStream learningStream mining
Most machine learning models are static, but the world is dynamic, and increasing online deployment of learned models gives increasing urgency to the development of efficient and effective mechanisms to address learning in the context of non-stationary distributions, or as it is commonly called concept drift. However, the key issue of cha...More
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