مورد إلكتروني
Boosted Poisson regression trees: A guide to the BT package in R
| العنوان: | Boosted Poisson regression trees: A guide to the BT package in R |
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| بيانات النشر: | 2023 |
| تفاصيل مُضافة: | UCL - SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles Willame, Gireg Trufin, Julien Denuit, Michel |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Thanks to its outstanding performances, boosting has rapidly gained wide acceptance among actuaries. Hainaut et al. (2022) established that boosting can be conducted directly on the response under Tweedie loss function and log-link, by adapting the weights at each step. This is particularly useful to analyze low counts (typically, numbers of reported claims at policy level in personal lines). Huyghe et al. (2022) adopted this approach to propose a new boosting machine with cost-complexity pruned trees. In this approach, trees included in the score progressively reduce to the root-node one, in an adaptive way. This paper reviews these results and presents the new BT package in R contributed by Willame (2022), which is designed to implement this approach for insurance studies. A numerical illustration demonstrates the relevance of the new tool for insurance pricing. |
| مصطلحات الفهرس: | Risk classification, Boosting, Adaptive Boosting, Regression Trees, info:eu-repo/semantics/workingPaper |
| URL: | |
| الإتاحة: | Open access content. Open access content info:eu-repo/semantics/openAccess |
| ملاحظة: | English |
| أرقام أخرى: | UCDLC oai:dial.uclouvain.be:boreal:273136 boreal:273136 LIDAM Discussion Paper ISBA 2023/08 1372921115 |
| المصدر المساهم: | UNIVERSITE CATHOLIQUE DE LOUVAIN From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1372921115 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |