On cognitive preferences and the plausibility of rule-based models

DOI10.1007/s10994-019-05856-5zbMath1496.68273arXiv1803.01316OpenAlexW2997133340MaRDI QIDQ782445

Tomáš Kliegr, Johannes Fürnkranz, Heiko Paulheim

Publication date: 27 July 2020

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1803.01316

zbMATH Keywords

cognitive biasinductive rule learninginterpretable models

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Cognitive psychology (91E10)

Related Items (1)

Editable machine learning models? A rule-based framework for user studies of explainability

Uses Software

• WordNet
• UCI-ml
• Stata
• arules
• word2vec
• somersd
• Krimp
• DeepRED

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