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Machine learning algorithms deployed for evolving streaming environments must handle the non-stationary data distributions, commonly referred to as concept drift. The presence of concept drift poses a major challenge for many real-world applications because it can severely degrade their predictive performance, hindering their ability to support robust decision-making.
ORIGINAL ARTICLE Samira Sadaoui Corresponding Author Samira.Sadaoui@uregina.ca orcid.org/0000-0002-9887-1570 Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada Correspondence Samira Sadaoui, Department of Computer Science, University of Regina, Regina, SK, Canada.
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