1 citations · 2 across the 6 of their papers we have counts for
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stat.ML2019
On the Insufficiency of the Large Margins Theory in Explaining the Performance of Ensemble Methods
Waldyn Martinez, J. Brian Gray
Boosting and other ensemble methods combine a large number of weak classifiers through weighted voting to produce stronger predictive models. To explain the successful performance…
stat.ML2019★ 1 cited
Ensemble Pruning via Margin Maximization
Waldyn Martinez
Ensemble models refer to methods that combine a typically large number of classifiers into a compound prediction. The output of an ensemble method is the result of fitting a base-l…
stat.ML2019★ 1 cited
On the Current State of Research in Explaining Ensemble Performance Using Margins
Waldyn Martinez, J. Brian Gray
Empirical evidence shows that ensembles, such as bagging, boosting, random and rotation forests, generally perform better in terms of their generalization error than individual cla…