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Christophe Mues
Christophe Mues
Professor of Data Science and Information Systems, University of Southampton
Verified email at soton.ac.uk - Homepage
Title
Cited by
Cited by
Year
Benchmarking classification models for software defect prediction: A proposed framework and novel findings
S Lessmann, B Baesens, C Mues, S Pietsch
IEEE transactions on software engineering 34 (4), 485-496, 2008
15532008
An experimental comparison of classification algorithms for imbalanced credit scoring data sets
I Brown, C Mues
Expert systems with applications 39 (3), 3446-3453, 2012
9312012
Using neural network rule extraction and decision tables for credit-risk evaluation
B Baesens, R Setiono, C Mues, J Vanthienen
Management science 49 (3), 312-329, 2003
7402003
An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models
J Huysmans, K Dejaeger, C Mues, J Vanthienen, B Baesens
Decision Support Systems 51 (1), 141-154, 2011
5702011
Building comprehensible customer churn prediction models with advanced rule induction techniques
W Verbeke, D Martens, C Mues, B Baesens
Expert systems with applications 38 (3), 2354-2364, 2011
5162011
Benchmarking regression algorithms for loss given default modeling
G Loterman, I Brown, D Martens, C Mues, B Baesens
International Journal of Forecasting 28 (1), 161-170, 2012
2552012
Recursive neural network rule extraction for data with mixed attributes
R Setiono, B Baesens, C Mues
IEEE transactions on neural networks 19 (2), 299-307, 2008
1902008
Mining software repositories for comprehensible software fault prediction models
O Vandecruys, D Martens, B Baesens, C Mues, M De Backer, R Haesen
Journal of Systems and software 81 (5), 823-839, 2008
1772008
Mixture cure models in credit scoring: If and when borrowers default
ENC Tong, C Mues, LC Thomas
European Journal of Operational Research 218 (1), 132-139, 2012
1732012
Inferring descriptive and approximate fuzzy rules for credit scoring using evolutionary algorithms
F Hoffmann, B Baesens, C Mues, T Van Gestel, J Vanthienen
European journal of operational research 177 (1), 540-555, 2007
1372007
An empirical comparison of classification algorithms for mortgage default prediction: evidence from a distressed mortgage market
T Fitzpatrick, C Mues
European Journal of Operational Research 249 (2), 427-439, 2016
1222016
50 years of data mining and OR: upcoming trends and challenges
B Baesens, C Mues, D Martens, J Vanthienen
Journal of the Operational Research Society 60 (sup1), S16-S23, 2009
1022009
Modelling LGD for unsecured personal loans: Decision tree approach
A Matuszyk, C Mues, LC Thomas
Journal of the Operational Research Society 61 (3), 393-398, 2010
992010
Domain knowledge integration in data mining using decision tables: case studies in churn prediction
E Lima, C Mues, B Baesens
Journal of the Operational Research Society 60 (8), 1096-1106, 2009
992009
A zero-adjusted gamma model for mortgage loan loss given default
ENC Tong, C Mues, L Thomas
International Journal of Forecasting 29 (4), 548-562, 2013
982013
The value of text for small business default prediction: A deep learning approach
M Stevenson, C Mues, C Bravo
European Journal of Operational Research 295 (2), 758-771, 2021
902021
Predicting loss given default (LGD) for residential mortgage loans: A two-stage model and empirical evidence for UK bank data
M Leow, C Mues
International Journal of Forecasting 28 (1), 183-195, 2012
872012
An illustration of verification and validation in the modelling phase of KBS development
J Vanthienen, C Mues, A Aerts
Data & Knowledge Engineering 27 (3), 337-352, 1998
691998
Ant-based approach to the knowledge fusion problem
D Martens, M De Backer, R Haesen, B Baesens, C Mues, J Vanthienen
Ant Colony Optimization and Swarm Intelligence: 5th International Workshop …, 2006
632006
Rule extraction from minimal neural networks for credit card screening
R Setiono, B Baesens, C Mues
International journal of neural systems 21 (04), 265-276, 2011
602011
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