SDDM: an interpretable statistical concept drift detection method for data streams
Machine learning models assume that data is drawn from a stationary distribution. However, in practice, challenges are imposed on models that need to make sense of fast-evolving data streams, where the content of data is changing and evolving over time. This change between the distributions of train...
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2021
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| Online Access: | https://bspace.buid.ac.ae/handle/1234/2929 https://link.springer.com/article/10.1007/s10844-020-00634-5 https://doi.org/10.1007/s10844-020-00634-5 |
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