TREE-BASED MACHINE LEARNING METHODS FOR MODELING AND FORECASTING MORTALITY

DOI10.1017/ASB.2022.11zbMath1504.91242OpenAlexW4280590933MaRDI QIDQ5045336

Dorethe Skovgaard Bjerre

Publication date: 4 November 2022

Published in: ASTIN Bulletin (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/asb.2022.11

zbMATH Keywords

mortalityrandom forestsgradient boostingstochastic mortality modelsmodel confidence set

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Actuarial mathematics (91G05)

Related Items (1)

Modelling socio-economic mortality at neighbourhood level

Uses Software

• randomForest
• ISLR
• MCS
• StMoMo

Cites Work

• Unnamed Item
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• Modelling and management of mortality risk: a review
• A NEURAL-NETWORK ANALYZER FOR MORTALITY FORECAST
• An Introduction to Statistical Learning
• Life expectancy and lifespan disparity forecasting: a long short-term memory approach
• A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States
• POINT AND INTERVAL FORECASTS OF DEATH RATES USING NEURAL NETWORKS
• Random forests
• Stochastic gradient boosting.

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