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A novel logistic regression model combining semi-supervised learning and active learning for disease classification
Traditional supervised learning classifier needs a lot of labeled samples to achieve good performance, however in many biological datasets there is only a small size of labeled samples and the remaining samples are unlabeled. Labeling these unlabeled samples manually is difficult or expensive. Techn...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6115447/ https://www.ncbi.nlm.nih.gov/pubmed/30158596 http://dx.doi.org/10.1038/s41598-018-31395-5 |