Characterizing Concept Drift

    Data Min. Knowl. Discov., Volume abs/1511.03816, Issue 4, 2016.

    Cited by: 79|Bibtex|Views24|Links
    EI
    Keywords:
    Concept driftLearning from non-stationary distributionsStream learningStream mining

    Abstract:

    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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