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Showing 1 to 2 of 2 for “"Stream learning"”.
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Improving ensembles and prediction intervals for machine learning on data streams
The rapid growth of streaming data presents significant challenges for traditional machine learning, including popular tasks like regression and classification. This thesis proposes adaptive and dynamic methods to address key issues, including concept drift, uncertainty quantification, and ensemble …
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Advanced adaptive classifier methods for data streams
… influx of big data. However, traditional batch learning models face significant obstacles in effectively learning from these vast and constantly evolving data streams and generating up-to-date outcomes. To overcome these limitations, Stream Learning (SL) has emerged as a promising solution that …