How do information and entropy propagate in hybrid (ensemble) machine learning?

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Generally, with the help of hybrid system, does the signal to noise ratio increase or decrease?

In ensemble learning the general idea is to combine a set of "weak" learners into a "strong" learner by weighted averaging. AdaBoost and related algorithms can be bounded in terms of their relative entropy (see e.g. Wang et al 2011) although the analysis is fairly involved.

http://jmlr.org/papers/volume12/wang11a/wang11a.pdf

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