An Empirical Comparison of Interpretable Models to Post-Hoc Explanations
Recently, some effort went into explaining intransparent and black-box models, such as deep neural networks or random forests. So-called model-agnostic methods typically approximate the prediction of the intransparent black-box model with an interpretable model, without considering any specifics of...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-05-01
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| Series: | AI |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-2688/4/2/23 |
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