Explainable Data Mining
Explainable Data Mining is a data mining approach that belongs to the class of knowledge discovery methods, distinguished by its explicit emphasis on generating human-interpretable models and results to ensure transparency, accountability, and trust in the discovered patterns.
56
Publications
4K
Citations
196
Authors
91
Institutions
Publications per year
2017–2026
29
Parents
56
Yasunobu Nohara, Koutarou Matsumoto, Hidehisa Soejima et al. · Computer Methods and Programs in Biomedicine · 2021 · 925 citations · Full text
Knowledge management and data mining for marketing
Michael Shaw, Chandrasekar Subramaniam, Gek Woo Tan et al. · Decision Support Systems · 2001 · 569 citations
1–5 of 56
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Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento, Portugal
2 publications · 50 citations
2
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2
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2
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1–5 of 196
91
University of Illinois Urbana-Champaign
Urbana, United States
3 h-index
7 publications
2.3K citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
6 publications
942 citations
University of Bergen
Bergen, Norway
2 h-index
8 publications
147 citations

Monash University
Melbourne, Australia
2 h-index
2 publications
50 citations

Nantong University
Nantong, China
2 h-index
2 publications
194 citations

The University of Melbourne
Melbourne, Australia
2 h-index
5 publications
73 citations

University of Waterloo
Waterloo, Canada
1 h-index
1 publications
33 citations

Central South University
Changsha, China
1 h-index
7 publications
147 citations
1–8 of 91
2 publications · 37 citations
2
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2 publications · 190 citations
2
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Repository · 2 publications · 34 citations
2
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1 publications · 17 citations
1
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JSEA · 1 publications · 11 citations
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1–5