Generating contrastive explanations for inductive logic programming based on a near miss approach

In recent research, human-understandable explanations of machine learning models have received a lot of attention. Often explanations are given in form of model simplifications or visualizations. However, as shown in cognitive science as well as in early AI research, concept understanding can also b...

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Veröffentlicht in:Machine learning Jg. 111; H. 5; S. 1799 - 1820
Hauptverfasser: Rabold, Johannes, Siebers, Michael, Schmid, Ute
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.05.2022
Springer Nature B.V
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ISSN:0885-6125, 1573-0565
Online-Zugang:Volltext
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