Interpretable by Design : Learning Predictors by Composing Interpretable Queries
There is a growing concern about typically opaque decision-making with high-performance machine learning algorithms. Providing an explanation of the reasoning process in domain-specific terms can be crucial for adoption in risk-sensitive domains such as healthcare. We argue that machine learning alg...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 45(2023), 6 vom: 28. Juni, Seite 7430-7443
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| 1. Verfasser: |
Chattopadhyay, Aditya
(VerfasserIn) |
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| Weitere Verfasser: |
Slocum, Stewart,
Haeffele, Benjamin D,
Vidal, Rene,
Geman, Donald |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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