Comparative Study on Class Imbalance Learning for Credit Scoring

Authors:
Ping Yao
Affiliations:
-
Venue:
HIS '09 Proceedings of the 2009 Ninth International Conference on Hybrid Intelligent Systems - Volume 02
Year:
2009

Citing 0
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Abstract

This paper performs systematic comparative studies on weighted methods including weight C4.5, weighted SVM and weighted rough set with traditional C4.5, SVM and rough set for credit scoring. The experiments show that the weighted methods outperform to the traditional methods when the methods are sensitive to the class distribution.