Ground Truth in Classification Accuracy Assessment: Myth and Reality
The ground reference dataset used in the assessment of classification accuracy is typically assumed implicitly to be perfect (i.e., 100% correct and representing ground truth). Rarely is this assumption valid, and errors in the ground dataset can cause the apparent accuracy of a classification to di...
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI AG
2024-02-01
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| Colección: | Geomatics |
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| Acceso en línea: | https://www.mdpi.com/2673-7418/4/1/5 |
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