Ensemble methods improve recommender accuracy by 0.3-5.7% but raise energy use by 19-2549%, with selective strategies being more efficient than full averaging.
Towards green recommender systems: Investigating the impact of data reduction on carbon footprint and algorithm performances,
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Ensembles at Any Cost? Accuracy-Energy Trade-offs in Recommender Systems
Ensemble methods improve recommender accuracy by 0.3-5.7% but raise energy use by 19-2549%, with selective strategies being more efficient than full averaging.