Rule Extraction
Rule Extraction is a machine learning interpretability method that derives symbolic rules from complex, opaque predictive models to approximate and explain their decision logic in human-understandable terms.
1.2K
Publications
73K
Citations
2.8K
Authors
1.1K
Institutions
Publications per year
2017–2026
242
Parents
1.2K
1–5 of 1.2K
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National University of Singapore
Singapore, Singapore
25 h-index
58 publications
4.8K citations

Universidad de Granada
Granada, Spain
17 h-index
41 publications
3.3K citations

Meiji University
Tokyo, Japan
16 h-index
36 publications
1.9K citations
Nanyang Technological University
Singapore, Singapore
14 h-index
31 publications
2.3K citations
KU Leuven
Leuven, Belgium
13 h-index
33 publications
4.7K citations

Indian Statistical Institute
Kolkata, India
12 h-index
19 publications
1.7K citations

University of Skövde
Skövde, Sweden
10 h-index
12 publications
437 citations
Osaka Prefecture University
Sakai, Japan
10 h-index
24 publications
1K citations
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TFS · 34 publications · 3.9K citations
28
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33 publications · 1.5K citations
25
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20 publications · 3K citations
20
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18 publications · 1.8K citations
16
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18 publications · 982 citations
16
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