On PAC-Bayesian bounds for random forests
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DOI: 10.1007/s10994-019-05803-4
Abstract: Existing guarantees in terms of rigorous upper bounds on the generalization error for the original random forest algorithm, one of the most frequently used machine learning methods, are unsatisfying. We discuss and evaluate various PAC-Bayesian… read more here.
Keywords: bayesian bounds; bounds random; random forests; taking majority ... See more keywords