2005
DOI: 10.1016/j.eswa.2005.01.004
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A comparison of supervised and unsupervised neural networks in predicting bankruptcy of Korean firms

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Cited by 183 publications
(72 citation statements)
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“…We note that this type of error is always very low in any of years studied, indeed it never exceeds 3.1%. These results are superior to those obtained in similar comparative analysis studies (Frydman et al, 1985;Koh Tan, 1999;Lennox, 1999;Min & Lee, 2005;Lee et al, 2005).…”
Section: Rough Setscontrasting
confidence: 55%
“…We note that this type of error is always very low in any of years studied, indeed it never exceeds 3.1%. These results are superior to those obtained in similar comparative analysis studies (Frydman et al, 1985;Koh Tan, 1999;Lennox, 1999;Min & Lee, 2005;Lee et al, 2005).…”
Section: Rough Setscontrasting
confidence: 55%
“…The sample population include 133 pairs of bankrupt and healthy firms accepted in South Korean stock exchange. Lee et al (2005) found that BP algorithm worked better than that of Kohonen. Doumpos et al (2005) adopted support vector machine in a sample including 1754 British firms in the period of 1998 to 2003 to create linear and nonlinear models for the prediction of the type of auditor's opinion.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Historical overview of model's creation is stated in table 1. The newest models are for example Ahn and Kim's hybrid case-based reasoning and genetic algorithm (Ahn & Kim, 2009), the model based on the neural networks (Lee, Booth & Alam, 2005), combination of random subspace approach and binary logit model (Li, Lee, Zhou & Sun, 2011), hazard model based model (Shumway, 2001). The newest Czech models are bankruptcy index with accuracy 80.28% (Karas & Režnáková, 2014) and the model created using the sample of plastic producers and metal manufacturing companies with accuracy 90.96% (Homolka, Doležal & Novák, 2014).…”
Section: Introductionmentioning
confidence: 99%