Aggregation Ordering in Bagging

@inproceedings{MartnezMuoz2004AggregationOI,
  title={Aggregation Ordering in Bagging},
  author={Gonzalo Martı́nez-Mu{\~n}oz and Alberto Su{\'a}rez},
  year={2004}
}
The order in which classifiers are aggregated in ensemble methods can be an important tool in the identification of subsets of classifiers that, when combined, perform better than the whole ensemble. Ensembles with randomly ordered classifiers usually exhibit a generalization error th at decreases as the number of classifiers that are aggregated increases. If an appropriate order for aggregation is chose n, the generalization error reaches, at intermediate numbers of classifiers, a minimum… CONTINUE READING
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