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In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone.^[1]^[2]^[3] Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.

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^ Rokach, L. (2010). "Ensemble-based classifiers". Artificial Intelligence Review. 33 (1–2): 1–39. doi:10.1007/s10462-009-9124-7. hdl:11323/1748. S2CID 11149239.