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Human Evaluation of Models Built for Interpretability
Recent years have seen a boom in interest in interpretable machine learning systems built on models that can be understood, at least to some degree, by domain experts. However, exactly what kinds of models are truly human-interpretable remains poorly understood. This work advances our understanding...
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| Publicado no: | Proc AAAI Conf Hum Comput Crowdsourc |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7899148/ https://ncbi.nlm.nih.gov/pubmed/33623933 |
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