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Boosting is more a generic methodology than as a particular method. It is based on the fact that more than training a single model, one could make use of several weak models (machine learning algorithms performing simply better than random procedures), each one trying to compensate the weaknesses of the predecessors.

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Boosting Algorithms

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Francisco Chinesta,
  • Elías Cueto,
  • Victor Champaney,
  • Chady Ghnatios,
  • Amine Ammar,
  • Nicolas Hascoët,
  • David González,
  • Icíar Alfaro,
  • Daniele Di Lorenzo,
  • Angelo Pasquale,
  • Dominique Baillargeat

摘要

Boosting is more a generic methodology than as a particular method. It is based on the fact that more than training a single model, one could make use of several weak models (machine learning algorithms performing simply better than random procedures), each one trying to compensate the weaknesses of the predecessors.