Gradient Boosting with Neural Networks

  • Michel Denuit
  • Donatien Hainaut
  • Julien Trufin
Part of the Springer Actuarial book series (SPACT)


Gradient boosting machines form a family of powerful machine learning techniques that have been applied with success in a wide range of practical applications. Ensemble techniques rely on simple averaging of models in the ensemble. The family of boosting methods adopts a different strategy to construct ensembles. In boosting algorithms, new models are sequentially added to the ensemble. At each iteration, a new weak base-learner is trained with respect to the error of the whole ensemble built so far.


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Authors and Affiliations

  • Michel Denuit
    • 1
  • Donatien Hainaut
    • 2
  • Julien Trufin
    • 3
  1. 1.Université Catholique LouvainLouvain-la-NeuveBelgium
  2. 2.Université Catholique de LouvainLouvain-la-NeuveFrance
  3. 3.Université Libre de BruxellesBrusselsBelgium

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