Predicting corporate financial distress based on integration of support vector machine and logistic regression

@article{Wang2007PredictingCF,
  title={Predicting corporate financial distress based on integration of support vector machine and logistic regression},
  author={Yu Wang and Xiaoyan Xu and Bin Zhang and Liang Liang},
  journal={Expert Syst. Appl.},
  year={2007},
  volume={33},
  pages={434-440}
}
The support vector machine (SVM) has been applied to the problem of bankruptcy prediction, and proved to be superior to competing methods such as the neural network, the linear multiple discriminant approaches and logistic regression. However, the conventional SVM employs the structural risk minimization principle, thus empirical risk of misclassification may be high, especially when a point to be classified is close to the hyperplane. This paper develops an integrated binary discriminant rule… CONTINUE READING
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