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Ideal Observers and Optimal ROC Hypersurfaces in N -Class Classification
The likelihood ratio, or ideal observer, decision rule is known to be optimal for two-class classification tasks in the sense that it maximizes expected utility (or, equivalently, minimizes the Bayes risk). Furthermore, using this decision rule yields a receiver operating characteristic (ROC) curve...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2004
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2464283/ https://ncbi.nlm.nih.gov/pubmed/15250641 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2004.828358 |
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