Metaheuristic-based ensemble learning: an extensive review of methods and applications
Sahar Saeed Rezk,
Kamal Samy Selim
Abstract:Ensemble learning has become a cornerstone in various classification and regression tasks, leveraging its robust learning capacity across disciplines. However, the computational time and memory constraints associated with almost all-learners-based ensembles necessitate efficient approaches. Ensemble pruning, a crucial step, involves selecting a subset of base learners to address these limitations. This study underscores the significance of optimization-based methods in ensemble pruning, with a specific focus o… Show more
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