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To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods
The main objective of eXplainable Artificial Intelligence (XAI) is to provide effective explanations for black-box classifiers. The existing literature lists many desirable properties for explanations to be useful, but there is a scarce consensus on how to quantitatively evaluate explanations in pra...
| 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/PMC8056245/ https://www.ncbi.nlm.nih.gov/pubmed/33977131 http://dx.doi.org/10.7717/peerj-cs.479 |