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Synthetic minority oversampling of vital statistics data with generative adversarial networks
OBJECTIVE: Minority oversampling is a standard approach used for adjusting the ratio between the classes on imbalanced data. However, established methods often provide modest improvements in classification performance when applied to data with extremely imbalanced class distribution and to mixed-typ...
Uloženo v:
| Vydáno v: | J Am Med Inform Assoc |
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| Hlavní autoři: | , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Oxford University Press
2020
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7750982/ https://ncbi.nlm.nih.gov/pubmed/32885818 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocaa127 |
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