{"id":5091,"date":"2025-03-13T13:05:29","date_gmt":"2025-03-13T13:05:29","guid":{"rendered":"https:\/\/detralytics.com\/?p=5091"},"modified":"2026-08-21T13:31:10","modified_gmt":"2026-08-21T13:31:10","slug":"boosting-on-the-responses-with-tweedie-and-binomial-loss-functions","status":"publish","type":"post","link":"https:\/\/detralytics.com\/fr\/publication\/boosting-on-the-responses-with-tweedie-and-binomial-loss-functions\/","title":{"rendered":"Boosting on the responses with tweedie and binomial loss functions"},"content":{"rendered":"
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Boosting on the responses with tweedie and binomial loss functions<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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DetraNote 2025-1<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\"Boosting\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Introduction<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Boosting emerged from the field of machine learning and became rapidly popular among insurance analysts. The Tweedie and Binomial distributions are the most commonly used in insurance for regression analysis. Hainaut et al. (2022) showed that boosting can be conducted directly on the response under Tweedie loss function and log-link, by adapting the weights at each iteration step. In this note, we recall the results of Hainaut et al. (2022) and we supplement them with an easy probabilistic interpretation to the boosting procedure. Next, we draw a parallel between these results and those established by Hastie et al. (2009) for the Bernoulli loss function and logit-link: Hastie et al. (2009) highlighted that, as an approximation, boosting can also be performed directly with responses under Bernoulli loss function and logit-link. Interestingly, we show that this observation can actually been extended to the Binomial case.<\/p>\n

Mots-cl\u00e9s : <\/span><\/strong>Clustering analysis, unsupervised learning, k-means, spectral clustering.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Secteur : <\/b>Assurance<\/p>\n

<\/b>Expertise: <\/b>Machine learning<\/p>\n

Auteurs :<\/b>\u00a0Julien Trufin<\/p>\n

\u00a0<\/p>\n

\u00c9diteur :<\/b> Detralytics<\/p>\n

Date:<\/b> March 2025<\/p>\n

Langue :<\/b> Anglais<\/p>\n

Pages:<\/b> 12<\/p>\n

Reference:<\/span>\u00a0Detra Note 2025-1<\/span><\/p>\n

\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\u00c0 propos des auteurs<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Julien\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Julien Trufin<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Julien est Scientific Advisor chez Detralytics et Professeur en sciences actuarielles au sein du d\u00e9partement de math\u00e9matiques de l\u2019Universit\u00e9 Libre de Bruxelles. Il poss\u00e8de une exp\u00e9rience en tant que consultant et un solide parcours acad\u00e9mique d\u00e9velopp\u00e9 au sein d\u2019institutions de renom, dont l\u2019Universit\u00e9 Laval (Canada), l\u2019UCL et l\u2019ULB (Belgique). Chez Detralytics, Julien encadre les jeunes talents, dispense des formations de pointe, stimule l\u2019innovation et supervise les projets de R&D.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t<\/path><\/svg>\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\tAll Publications<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

L’\u00e9mergence du boosting dans le domaine du machine learning a rapidement gagn\u00e9 en popularit\u00e9 parmi les actuaires. Les distributions de Tweedie (dont la Poisson, la Gamma) et binomiale sont les plus couramment utilis\u00e9es en assurance par exemple pour les mod\u00e8les de tarification.<\/p>","protected":false},"author":1,"featured_media":5094,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[133],"tags":[],"class_list":["post-5091","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publication"],"yoast_head":"\nDetra Note : Insurance Analytics with Clustering Techniques<\/title>\n<meta name=\"description\" content=\"This working note starts with a review of the k-means algorithm and develops next two extensions to manage categorical features.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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