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Estimating classification accuracy in positive-unlabeled learning: characterization and correction strategies
Accurately estimating performance accuracy of machine learning classifiers is of fundamental importance in biomedical research with potentially societal consequences upon the deployment of best-performing tools in everyday life. Although classification has been extensively studied over the past deca...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417800/ https://www.ncbi.nlm.nih.gov/pubmed/30864316 |