Active learning for clinical text classification: is it better than random sampling?
Objective: This study explores active learning algorithms as a way to reduce the requirements for large training sets in medical text classification tasks.Design: Three existing active learning algorithms (distance-based (DIST), diversity-based (DIV), and a combination of both (CMB)) were used to cl...
| Publicado en: | Journal of the American Medical Informatics Association Vol. 19; no. 5; pp. 809 - 817 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Oxford University Press / USA
Sep2012
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| Acceso en línea: | Ver este registro en EBSCOhost |