Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
384236 | Expert Systems with Applications | 2010 | 8 Pages |
Abstract
Bankruptcy prediction is one of the major business classification problems. In this paper, we use four different techniques (1) logit model, (2) quadratic interval logit model, (3) backpropagation multi-layer perceptron (i.e., MLP), and (4) radial basis function network (i.e., RBFN) to predict bankrupt and non-bankrupt firms in England. The average hit ratio of four methods range from 91.15% to 77.05%. The original classification accuracy and the validation test results indicate that RBFN outperforms the other models.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Fang-Mei Tseng, Yi-Chung Hu,