JICCE (한국정보통신학회)
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| 한글제목(Korean Title) |
Optimizing SVM Ensembles Using Genetic Algorithms in Bankruptcy Prediction |
| 영문제목(English Title) |
Optimizing SVM Ensembles Using Genetic Algorithms in Bankruptcy Prediction |
| 저자(Author) |
Myoung-Jong Kim
Hong-Bae Kim
Dae-Ki Kang
|
| 원문수록처(Citation) |
VOL 08 NO. 04 PP. 0370 ~ 0376 (2010. 08) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Ensemble learning is a method for improving the performance of classification and prediction algorithms. However, its performance can be degraded due to multicollinearity problem where multiple classifiers of an ensemble are highly correlated with. This paper proposes genetic algorithm-based optimization techniques of SVM ensemble to solve multicollinearity problem. Empirical results with bankruptcy prediction on Korea firms indicate that the proposed optimization techniques can improve the performance of SVM ensemble. |
| 키워드(Keyword) |
Bankruptcy Prediction
Coverage Optimization
Ensemble
Genetic Algorithm
Support Vector Machines
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| 파일첨부 |
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