9th Joint International Conference on Information Sciences (JCIS-06)

Genetic Programming Decision Tree for Bankruptcy Prediction

Authors
Wo-Chiang Lee 0
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Wo-Chiang Lee
0AI-Econ Research Group
DOI
https://doi.org/10.2991/jcis.2006.8How to use a DOI?
Keywords
Financial distress model, decision tree, GP decision tree
Abstract
In this paper, we apply the CART ,C5.0 , GP decision tree classifiers and compares with logic model and ANN model for Taiwan listed electronic companies bankruptcy prediction. Results reveal that the GP decision tree can outperform all the classifiers either in overall percentage of correct or k-fold cross validation test in out sample. That is to say, GP decision tree model have the highest accuracy and lowest expected misclassification costs. It can provide an efficient alternative to discriminates financial distress problems in Taiwan.
Copyright
© The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/
Open Access | Under Creative Commons license CC BY-NC 4.0

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@inproceedings{Lee2006,
  title={Genetic Programming Decision Tree for Bankruptcy Prediction},
  author={Lee, Wo-Chiang},
  year={2006},
  booktitle={9th Joint International Conference on Information Sciences (JCIS-06)},
  issn={1951-6851},
  isbn={978-90-78677-01-7},
  url={http://dx.doi.org/10.2991/jcis.2006.8},
  doi={10.2991/jcis.2006.8},
  publisher={Atlantis Press}
}
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