Interpretable Churn Models
Interpretable Churn Models is a class of predictive modeling frameworks in customer churn prediction that belong to the broader category of machine learning models but are specifically designed to provide transparent, human-understandable representations of the factors and decision logic influencing churn predictions.
11
Publications
803
Citations
39
Authors
29
Institutions
Publications per year
2017–2026
6
Parents
11
Carl Yang, Xiaolin Shi, Luo Jie et al. · 2018 · 84 citations
Churn Prediction in MMORPGs Using Player Motivation Theories and an Ensemble Approach
Zoheb Borbora, Jaideep Srivastava, Kuo-Wei Hsu et al. · 2011 · 56 citations
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Institut d'Economie Scientifique Et de Gestion
Puteaux, France
2 h-index
2 publications
115 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
2 publications
115 citations

Ghent University
Ghent, Belgium
2 h-index
3 publications
493 citations
University of Southampton
Southampton, United Kingdom
1 h-index
2 publications
714 citations

Beijing University of Posts and Telecommunications
Beijing, China
1 h-index
4 publications
88 citations
KU Leuven
Leuven, Belgium
1 h-index
3 publications
1.1K citations

National Chengchi University
Taipei, Taiwan
1 h-index
1 publications
56 citations
Dalian University of Technology
Dalian, China
1 h-index
1 publications
60 citations
1–8 of 29
2 publications · 425 citations
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1 publications · 38 citations
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1 publications · 60 citations
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1 publications · 47 citations
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1 publications · 26 citations
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