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Classifier uncertainty: evidence, potential impact, and probabilistic treatment
Classifiers are often tested on relatively small data sets, which should lead to uncertain performance metrics. Nevertheless, these metrics are usually taken at face value. We present an approach to quantify the uncertainty of classification performance metrics, based on a probability model of the c...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
PeerJ Inc.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959610/ https://www.ncbi.nlm.nih.gov/pubmed/33817044 http://dx.doi.org/10.7717/peerj-cs.398 |