Abstract
We propose a novel approach to finding explanations of deviating subsets, often called subgroups. Existing approaches for subgroup discovery rely on various quality measures that nonetheless often fail to find subgroup sets that are diverse, of high quality, and most importantly, provide good explanations of the deviations that occur in the data.
Original language | English |
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Title of host publication | Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II |
Editors | Michelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, Saso Dzeroski |
Number of pages | 17 |
Place of Publication | Cham |
Publisher | Springer International Publishing AG |
Publication date | 30 Dec 2017 |
Pages | 425-441 |
ISBN (Print) | 978-3-319-71245-1 |
ISBN (Electronic) | 978-3-319-71246-8 |
DOIs | |
Publication status | Published - 30 Dec 2017 |
MoE publication type | A4 Article in conference proceedings |
Event | European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - Skopje, Macedonia, The Former Yugoslav Republic of Duration: 18 Sept 2017 → 22 Sept 2017 http://ecmlpkdd2017.ijs.si |
Publication series
Name | Lecture Notes in Artificial Intelligence |
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Publisher | Springer International Publishing AG |
Volume | 10535 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Fields of Science
- 113 Computer and information sciences