2021
DOI: 10.48550/arxiv.2110.03540
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A Broad Ensemble Learning System for Drifting Stream Classification

Abstract: Data stream classification has become a major research topic due to the increase in temporal data. One of the biggest hurdles of data stream classification is the development of algorithms that deal with evolving data, also known as concept drifts. As data changes over time, static prediction models lose their validity. Adapting to concept drifts provides more robust and better performing models. The Broad Learning System (BLS) is an effective broad neural architecture recently developed for incremental learni… Show more

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“…Broad Ensemble Learning System (BELS), a stream classification method based on the original BELS, introduced in [ 38 ], leverages a dynamic output ensemble layer to overcome its limitations. However, it cannot operate with semi-supervised learning.…”
Section: Literature Surveymentioning
confidence: 99%
“…Broad Ensemble Learning System (BELS), a stream classification method based on the original BELS, introduced in [ 38 ], leverages a dynamic output ensemble layer to overcome its limitations. However, it cannot operate with semi-supervised learning.…”
Section: Literature Surveymentioning
confidence: 99%