A self-inspected adaptive SMOTE algorithm (SASMOTE) for highly imbalanced data classification in healthcare

In many healthcare applications, datasets for classification may be highly imbalanced due to the rare occurrence of target events such as disease onset. The SMOTE (Synthetic Minority Over-sampling Technique) algorithm has been developed as an effective resampling method for imbalanced data classific...

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Detalles Bibliográficos
Autores principales: Kosolwattana, Tanapol, Liu, Chenang, Hu, Renjie, Han, Shizhong, Chen, Hua, Lin, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131309/
https://www.ncbi.nlm.nih.gov/pubmed/37098549
http://dx.doi.org/10.1186/s13040-023-00330-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131309/
https://www.ncbi.nlm.nih.gov/pubmed/37098549
http://dx.doi.org/10.1186/s13040-023-00330-4

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