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          FAQctuary 2020-1 : Features with flat partial dependence plots: not important?
          02/04/2020
          Detralytics is officially an IABE accredited trainer
          10/05/2020
          Detranote_2020-02 - Algorithmes d'apprentissage_Page_01
          Detra Note 2020-2
          Quelles limites pour l'application des algorithmes d'apprentissage en assurance ?

          Dans cette nouvelle Detra Note, Arthur Charpentier et Michel Denuit évoquent les limites de l’application des algorithmes prédictifs en assurance en revenant sur les notions de segmentation des risques et d’hétérogénéité.

          Une étape essentielle du processus de tarification est le choix de l'algorithme qui permettra de calculer la prime à partir de données passées.

          En assurance, les modèles prédictifs sont partout : il peut s'agir de calculer la prime demandée pour couvrir les dommages causés à un bien, ou encore d'un score interne de suspicion de fraude sur un sinistre.
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