Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 37, Issue 4, Pages 3373-3379Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2009.10.012
Keywords
Boosting; Bagging; Neural networks; Bankruptcy prediction
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In a bankruptcy prediction model, the accuracy is one of crucial performance measures due to its significant economic impact. Ensemble is one of widely used methods for improving the performance of classification and prediction models. Two popular ensemble methods, Bagging and Boosting, have been applied with great success to various machine learning problems using mostly decision trees as base classifiers. In this paper, we propose an ensemble with neural network for improving the performance of traditional neural networks on bankruptcy prediction tasks. Experimental results on Korean firms indicated that the bagged and the boosted neural networks showed the improved performance over traditional neural networks. (C) 2009 Elsevier Ltd. All rights reserved.
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