Assessing environmental determinants of subjective well-being via machine learning approaches: a systematic review
Abstract Understanding the determinants of subjective well-being (SWB) is crucial for advancing social sciences, particularly in relation to environmental and social factors. Machine learning (ML) techniques have gained popularity in SWB research, yet there is limited synthesis of their current impl...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer Nature
2025-06-01
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| Series: | Humanities & Social Sciences Communications |
| Online Access: | https://doi.org/10.1057/s41599-025-05234-8 |
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