BANKRUPTCY PREDICTION USING CASE-BASED REASONING, NEURAL NETWORKS, AND DISCRIMINANT-ANALYSIS

Authors
JO HK HAN IG LEE HY
Citation
Hk. Jo et al., BANKRUPTCY PREDICTION USING CASE-BASED REASONING, NEURAL NETWORKS, AND DISCRIMINANT-ANALYSIS, Expert systems with applications, 13(2), 1997, pp. 97-108
Citations number
32
Categorie Soggetti
Operatione Research & Management Science","System Science","Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence
Journal title
Expert systems with applications → ACNP
ISSN journal
09574174
Volume
13
Issue
2
Year of publication
1997
Pages
97 - 108
Database
ISI
SICI code
0957-4174(1997)13:2<97:BPUCRN>2.0.ZU;2-W
Abstract
Bankruptcy prediction is one of the major business classification prob lems. In this paper we use three different techniques: (1) Multivariat e discriminant analysis, (2) case-based forecasting, and (3) neural ne twork to predict Korean bankrupt and nonbankrupt firms. The average hi t ratios of three methods range from 81.5 to 83.8%. Neural network per forms better allan discriminant analysis and the case-based forecastin g system. (C) 1997 Elsevier Science Ltd.