It is well known that combining the output of several rules results in much better performance than using any one of them alone. In fact many state-of-the-art algorithms search for a weighted combination of simpler rules [1]: Bagging [2, 3], Boosting [4, 5] and Bayesian approaches [6] or even Kernel methods [7] and Neural Networks [8].
PAC-Bayes Theory
Oneto L.
2020-01-01
Abstract
It is well known that combining the output of several rules results in much better performance than using any one of them alone. In fact many state-of-the-art algorithms search for a weighted combination of simpler rules [1]: Bagging [2, 3], Boosting [4, 5] and Bayesian approaches [6] or even Kernel methods [7] and Neural Networks [8].
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