Generalization error for Tweedie models: decomposition and error reduction with bagging

Michel Denuit and Julien Trufin
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Michel Denuit: Université catholique de Louvain, LIDAM/ISBA, Belgium
Julien Trufin: Université Libre de Bruxelles

No 2021025, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: Wüthrich and Buser (DOI:10.2139/ssrn.2870308, 2020) studied the generalization error for Poisson regression models. This short note aims to extend their results to the Tweedie family of distributions, to which the Poisson law belongs. In case of bagging, a new condition emerges that becomes increasingly binding with the power parameter involved in the Tweedie variance function.

Keywords: Generalization error; Supervised learning; Exponential dispersion family; Tweedie; Bagging (search for similar items in EconPapers)
Pages: 7
Date: 2021-02-08
Note: In: European Actuarial Journal, 2021, vol. 11, p. 325-331
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2021025

DOI: 10.1007/s13385-021-00265-2

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