Interpretable machine learning methods to explain on-farm yield variability of high productivity wheat in Northwest India
The increasing availability of complex, geo-referenced on-farm data demands analytical frameworks that can guide crop management recommendations. Recent developments in interpretable machine learning techniques offer opportunities to use these methods in agronomic studies. Our objectives were two-fo...
| Autores principales: | , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/127194 |
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