Machine learning in the prediction of human wellbeing

Abstract Subjective wellbeing data are increasingly used across the social sciences. Yet, despite the widespread use of such data, the predictive power of approaches commonly used to model wellbeing is only limited. In response, we here use tree-based Machine Learning (ML) algorithms to provide a be...

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Bibliographic Details
Main Authors: Ekaterina Oparina, Caspar Kaiser, Niccolò Gentile, Alexandre Tkatchenko, Andrew E. Clark, Jan-Emmanuel De Neve, Conchita D’Ambrosio
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-024-84137-1
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