Boosting cost-complexity pruned trees on Tweedie responses: the ABT machine for insurance ratemaking
Author:
Affiliation:
1. Department of Mathematics, Université Libre de Bruxelles (ULB), Brussels, Belgium
2. Institute of Statistics, Biostatistics and Actuarial Science, UCLouvain, Louvain-la-Neuve, Belgium
Publisher
Informa UK Limited
Subject
Statistics, Probability and Uncertainty,Economics and Econometrics,Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/03461238.2023.2258135
Reference24 articles.
1. Breiman, L., Friedman, J. H., Olshen, R. A. & Stone, C. J. (1984). Classification and Regression Trees. Boca Raton, FL: CRC Press.
2. Predictive ensemble pruning by expectation propagation;Chen H.;IEEE Transactions on Knowledge and Data Engineering,2009
3. Recent advances in decision trees: An updated survey;Costa V. G.;Artificial Intelligence Review,2022
4. Denuit M. Hainaut D. & Trufin J. (2019a). Effective statistical learning methods for actuaries I: GLM and extensions . Springer Actuarial Lecture Notes Series. Cham: Springer.
5. Denuit M. Hainaut D. & Trufin J. (2019b). Effective statistical learning methods for actuaries III: Neural networks and extensions . Springer Actuarial Lecture Notes Series. Cham: Springer.
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1. Boosted Poisson regression trees: a guide to the BT package in R;Annals of Actuarial Science;2024-01-15
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