Machine learning techniques for mortality modeling

Philippe Deprez; Pavel V. Shevchenko; Mario V. Wüthrich

doi:10.2139/ssrn.2921841

Machine learning techniques for mortality modeling

Philippe Deprez^*, Pavel V. Shevchenko, Mario V. Wüthrich

^*Corresponding author for this work

Department of Applied Finance

Research output: Contribution to journal › Article

10 Citations (Scopus)

Abstract

Various stochastic models have been proposed to estimate mortality rates. In this paper we illustrate how machine learning techniques allow us to analyze the quality of such mortality models. In addition, we present how these techniques can be used for differentiating the different causes of death in mortality modeling.

Original language	English
Pages (from-to)	337-352
Number of pages	16
Journal	European Actuarial Journal
Volume	7
Issue number	2
DOIs	https://doi.org/10.2139/ssrn.2921841 https://doi.org/10.1007/s13385-017-0152-4
Publication status	Published - 1 Dec 2017

Keywords

mortality modeling
cause-of-death mortality
machine learning
boosting
regression

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title = "Machine learning techniques for mortality modeling",

abstract = "Various stochastic models have been proposed to estimate mortality rates. In this paper we illustrate how machine learning techniques allow us to analyze the quality of such mortality models. In addition, we present how these techniques can be used for differentiating the different causes of death in mortality modeling.",

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KW - boosting

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