Explainability and Interpretability in Concept and Data Drift: A Systematic Literature Review
Explainability and interpretability have emerged as essential considerations in machine learning, particularly as models become more complex and integral to a wide range of applications. In response to increasing concerns over opaque “black-box” solutions, the literature has seen a shift toward two...
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| Principais autores: | , , |
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| Format: | Artigo |
| Sprog: | Inglês |
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MDPI AG
2025-07-01
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| Serier: | Algorithms |
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| Online adgang: | https://www.mdpi.com/1999-4893/18/7/443 |
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