Abstract
Wüthrich and Buser 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
Sector: Insurance
Authors: Michel Denuit and
Julien Trufin
Publication: European Actuarial
Journal
Date: February 2021
Language: English
About the authors
Michel Denuit
Michel is an Honorary Scientific Advisor at Detralytics, as well as a professor in actuarial science at the Université Catholique de Louvain. He has international experience as a visiting professor, and has promoted many projects in collaboration with the industry. At Detralytics, Michel coaches young talents, provides cutting-edge training, fosters innovation and oversees R&D projects.
Julien Trufin
Julien is a Scientific Advisor at Detralytics, as well as a professor in Actuarial Science at the department of mathematics of the Université Libre de Bruxelles. Julien has experience as a consultant and a strong academic background developed at prominent institutions, including Université Laval (Canada), UCL, and ULB (Belgium). At Detralytics, Julien coaches young talents, provide cutting-edge training, fosters innovation and oversees R&D projects.
