Effective Class-Imbalance Learning Based on SMOTE and Convolutional Neural Networks
Imbalanced Data (ID) is a problem that deters Machine Learning (ML) models from achieving satisfactory results. ID is the occurrence of a situation where the quantity of the samples belonging to one class outnumbers that of the other by a wide margin, making such models’ learning process biased towa...
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| Autores principales: | , , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI AG
2023-03-01
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| Colección: | Applied Sciences |
| Materias: | |
| Acceso en línea: | https://www.mdpi.com/2076-3417/13/6/4006 |
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