High accuracy prediction of Thai rice glycemic index using machine learning
This study investigated the effectiveness of machine learning (ML) models in estimating the glycemic index (GI) of Thai rice starches from their physicochemical characteristics. Three models, XGBoost, CatBoost and RandomForest, were employed on a dataset comprising various starch properties. All mod...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | Cogent Food & Agriculture |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/23311932.2024.2411032 |
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