Corpus ID: 6463323

Pruning Adaptive Boosting *** Icml-97 Final Draft ***

@inproceedings{Dietterich2015PruningAB,
  title={Pruning Adaptive Boosting *** Icml-97 Final Draft ***},
  author={Thomas G. Dietterich},
  year={2015}
}
The boosting algorithm AdaBoost de veloped by Freund and Schapire has ex hibited outstanding performance on sev eral benchmark problems when using C as the weak algorithm to be boosted Like other ensemble learning approaches AdaBoost constructs a composite hy pothesis by voting many individual hy potheses In practice the large amount of memory required to store these hypotheses can make ensemble methods hard to deploy in applications This paper shows that by selecting a subset of the hypotheses… Expand
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