Enhancing poverty classification in developing countries through machine learning: a case study of household consumption prediction in Rwanda
To address the challenges associated with measuring and classifying household consumption (poverty) in developing countries, such as cost, time gaps, and inaccurate socio-economic data, this study suggests leveraging machine learning (ML) algorithms. We assessed the performance of various ML algorit...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Cogent Economics & Finance |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/23322039.2024.2444374 |
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