A feature restoration for machine learning on anti-corrosion materials
Materials informatics often struggles with small datasets. Our study introduces the Gaussian Mixture Model Virtual Sample Generation (GMM-VSG) approach to enhance feature correlation by generating virtual samples. Applied to six small and one large dataset of 218 N-heterocyclic compounds, GMM-VSG si...
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| Главные авторы: | , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Elsevier
2024-12-01
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| Серии: | Case Studies in Chemical and Environmental Engineering |
| Предметы: | |
| Online-ссылка: | http://www.sciencedirect.com/science/article/pii/S2666016424002962 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
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