00764nam0-22002411i-450-990001213100403321000121310FED01000121310(Aleph)000121310FED0100012131020000920d1989----km-y0itay50------baengProbability Theory on Vector SpacesProceedings of a Conference, held in Lancust, Poland, June 10-17, 1987Eds S. Cambanis , A. Weron.Berlin [etc.]Springer-Verlag1989Lecture Notes in Mathematics1391ITUNINARICAUNIMARCBK990001213100403321C-20-(13915961MA1MA1Probability theory on vector spaces80532UNINAING0102823oam 2200505 450 99641818260331620210618120151.03-030-57556-X10.1007/978-3-030-57556-4(CKB)4100000011586001(DE-He213)978-3-030-57556-4(MiAaPQ)EBC6455952(PPN)252509145(EXLCZ)99410000001158600120210618d2020 uy 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierEffective statistical learning methods for actuatriesIITree-based methods and extensions /Michel Denuit, Donatien Hainaut, Julien Trufin1st ed. 2020.Cham, Switzerland :Springer,[2020]©20201 online resource (X, 228 p. 68 illus., 6 illus. in color.) Springer Actuarial Lecture Notes,2523-32703-030-57555-1 Chapter 1: Introductio -- Chapter 2 : Performance Evaluation -- Chapter 3 Regression Trees -- Chapter 4 Bagging Trees and Random Forests -- Chapter 5 Boosting Trees -- Chapter 6 Other Measures for Model Comparison.This book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods. It also exhibits the tools which make it possible to assess the predictive performance of tree-based models. Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and numerical illustrations or case studies. All numerical illustrations are performed with the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. In particular, masters students in actuarial sciences and actuaries wishing to update their skills in machine learning will find the book useful. This is the second of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance.Springer Actuarial Lecture Notes,2523-3289Regression analysisActuarial scienceRegression analysis.Actuarial science.519.536Denuit Michel781288Hainaut DonatienTrufin JulienMiAaPQMiAaPQUtOrBLWBOOK996418182603316Effective statistical learning methods for actuatries2243027UNISA