Boosted Poisson regression trees: A guide to the BT package in R
(2023) , 26 pages
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- Abstract
- 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.
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Citations
Willame, G., Trufin, J., & Denuit, M. (2023). Boosted Poisson regression trees: A guide to the BT package in R (LIDAM Discussion Paper ISBA 2023/08). https://hdl.handle.net/2078.5/101163