Bankruptcy prediction using case-based reasoning, neural networks, and discriminant analysis
Expert Systems with ApplicationsPublished 1 August 1997
Hongkyu Jo, Ingoo Han, Hoonyoung Lee
Citations272
SJR quartileQ1
SJR score1.85
SNIP2.55
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TL;DR
Three different techniques are used: Multivariate discriminant analysis, case-based forecasting, and neural network to predict Korean bankrupt and nonbankrupt firms, with good results.
Abstract
Bankruptcy prediction is one of the major business classification problems. 1n this paper, we use three different techniques: (1) Multivariate discriminant analysis, (2) case-based forecasting, and (3) neural network to predict Korean bankrupt and nonbankrupt firms. The average hit ratios of three methods range from 81.5 to 83.8%. Neural network performs better than discriminant analysis and the case-based forecasting system.
Keywords
Computer ScienceBusiness, Management and Accounting
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