Drift mining in data: A framework for addressing drift in classification
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DOI: 10.1016/j.csda.2012.07.007
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References listed on IDEAS
- I. D. Currie & M. Durban & P. H. C. Eilers, 2006. "Generalized linear array models with applications to multidimensional smoothing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(2), pages 259-280, April.
- Hand D.J. & Vinciotti V., 2003. "Local Versus Global Models for Classification Problems: Fitting Models Where it Matters," The American Statistician, American Statistical Association, vol. 57, pages 124-131, May.
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Cited by:
- Hofer, Vera, 2015. "Adapting a classification rule to local and global shift when only unlabelled data are available," European Journal of Operational Research, Elsevier, vol. 243(1), pages 177-189.
- Dirk Tasche, 2014. "Exact fit of simple finite mixture models," Papers 1406.6038, arXiv.org, revised Jul 2014.
- Dirk Tasche, 2014. "Exact Fit of Simple Finite Mixture Models," JRFM, MDPI, vol. 7(4), pages 1-15, November.
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Keywords
Concept drift; Verification latency; Drift mining;All these keywords.
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