On the suitability of resampling techniques for the class imbalance problem in credit scoring
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Altres documents de l'autoria: Marqués Marzal, Ana Isabel; García, Vicente; Sánchez Garreta, Josep Salvador
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Títol
On the suitability of resampling techniques for the class imbalance problem in credit scoringData de publicació
2013Editor
Palgrave MacmillanISSN
0160-5682; 1476-9360Cita bibliogràfica
MARQUÉS, A. I.; GARCÍA, V.; SÁNCHEZ, J. S. On the suitability of resampling techniques for the class imbalance problem in credit scoring. Journal of the Operational Research Society, 2012, vol. 64, no 7, p. 1060-1070Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
http://www.palgrave-journals.com/jors/journal/v64/n7/full/jors2012120a.htmlVersió
info:eu-repo/semantics/acceptedVersionParaules clau / Matèries
Resum
In real-life credit scoring applications, the case in which the class of defaulters is under-represented in comparison with the class of non-defaulters is a very common situation, but it has still received little ... [+]
In real-life credit scoring applications, the case in which the class of defaulters is under-represented in comparison with the class of non-defaulters is a very common situation, but it has still received little attention. The present paper investigates the suitability and performance of several resampling techniques when applied in conjunction with statistical and artificial intelligence prediction models over five real-world credit data sets, which have artificially been modified to derive different imbalance ratios (proportion of defaulters and non-defaulters examples). Experimental results demonstrate that the use of resampling methods consistently improves the performance given by the original imbalanced data. Besides, it is also important to note that in general, over-sampling techniques perform better than any under-sampling approach. [-]
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Journal of the Operational Research Society (2012), vol. 64, no 7Drets d'accés
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