Predicting poverty and malnutrition for targeting, mapping, monitoring, and early warning
Increasingly plentiful data and powerful predictive algorithms heighten the promise of data science for humanitarian and development programming. We advocate for embrace of, and investment in, machine learning methods for poverty and malnutrition targeting, mapping, monitoring, and early warning whi...
| Autores principales: | , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Agricultural and Applied Economics Association
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/141111 |
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