SMOTE-BD: An Exact and Scalable Oversampling Method for Imbalanced Classification in Big Data
The volume of data in today’s applications has meant a change in the way Machine Learning issues are addressed. Indeed, the Big Data scenario involves scalability constraints that can only be achieved through intelligent model design and the use of distributed technologies. In this context, solutio...
Guardado en:
| Autores principales: | Basgall, María José, Hasperué, Waldo, Naiouf, Marcelo, Fernández, Alberto, Herrera, Francisco |
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| Formato: | Articulo |
| Lenguaje: | Inglés |
| Publicado: |
2018
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/71652 http://journal.info.unlp.edu.ar/JCST/article/view/1122 |
| Aporte de: |
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