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Comment améliorer la capacité de généralisation des algorithmes d'apprentissage pour la prise de décisions financières

Author

Listed:
  • Nicolas Chapados
  • Yoshua Bengio

Abstract

This report presents and proposes several methods to improve the capacity of generalization of the learning algorithms in a context of financial decision-making. These methods, overall, aim at controlling the capacity of the learning algorithms in order to limit the problem of the over-training, which is one of most pernicious in finance because of the high levels of noise met in practice. We propose some tracks of research in order to improve the algorithms and results already obtained. Ce rapport présente et propose plusieurs méthodes pour améliorer la capacité de généralisation des algorithmes d'apprentissage dans un contexte de prise de décisions financières. Globalement, ces méthodes visent à contrôler la capacité des algorithmes d'apprentissage en vue de limiter le problème du sur-apprentissage, qui est l'un des plus pernicieux en finance à cause des niveaux de bruit élevés rencontrés en pratique. Nous proposons quelques pistes de recherches afin d'améliorer les algorithmes et résultats déjà obtenus.

Suggested Citation

  • Nicolas Chapados & Yoshua Bengio, 2003. "Comment améliorer la capacité de généralisation des algorithmes d'apprentissage pour la prise de décisions financières," CIRANO Working Papers 2003s-20, CIRANO.
  • Handle: RePEc:cir:cirwor:2003s-20
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    File URL: https://cirano.qc.ca/files/publications/2003s-20.pdf
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