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Counterfactual Models for Fair and Adequate Explanations

Recent efforts have uncovered various methods for providing explanations that can help interpret the behavior of machine learning programs. Exact explanations with a rigorous logical foundation provide valid and complete explanations, but they have an epistemological problem: they are often too comp...

Ausführliche Beschreibung

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Bibliografische Detailangaben
Hauptverfasser: Nicholas Asher, Lucas De Lara, Soumya Paul, Chris Russell
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2022-03-01
Schriftenreihe:Machine Learning and Knowledge Extraction
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Online-Zugang:https://www.mdpi.com/2504-4990/4/2/14
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