DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박정민 | ko |
dc.contributor.author | 김경재 | ko |
dc.contributor.author | 한인구 | ko |
dc.date.accessioned | 2011-01-12T07:14:00Z | - |
dc.date.available | 2011-01-12T07:14:00Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2005-06 | - |
dc.identifier.citation | ASIA PACIFIC JOURNAL OF INFORMATION SYSTEMS, v.15, no.2, pp.51 - 63 | - |
dc.identifier.issn | 1229-0270 | - |
dc.identifier.uri | http://hdl.handle.net/10203/21562 | - |
dc.description.abstract | There has been substantial research into the bankruptcy prediction. Many researchers used the statistical method in the problem until the early 1980s. Since the late 1980s, Artificial Intelligence(AI) has been employed in bankruptcy prediction. And many studies have shown that artificial neural network(ANN) achieved better performance than traditional statistical methods. However, despite ANNs superior performance, it has some problems such as overfitting and poor explanatory power. To overcome these limitations, this paper suggests a relatively new machine learning technique, support vector machine(SVM), to bankruptcy prediction. SVM is simple enough to be analyzed mathematically, and leads to high performances in practical applications. The objective of this paper is to examine the feasibility of SVM in bankruptcy prediction by comparing it with ANN, logistic regression, and multivariate discriminant analysis. The experimental results show that SVM provides a promising alternative to bankruptcy prediction. | - |
dc.language | Korean | - |
dc.language.iso | ko | en |
dc.publisher | 한국경영정보학회 | - |
dc.title | Support Vector Machine을 이용한 기업부도예측 | - |
dc.title.alternative | Bankruptcy Prediction using Support Vector Machines | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 15 | - |
dc.citation.issue | 2 | - |
dc.citation.beginningpage | 51 | - |
dc.citation.endingpage | 63 | - |
dc.citation.publicationname | ASIA PACIFIC JOURNAL OF INFORMATION SYSTEMS | - |
dc.embargo.liftdate | 9999-12-31 | - |
dc.embargo.terms | 9999-12-31 | - |
dc.identifier.kciid | ART000964450 | - |
dc.contributor.localauthor | 한인구 | - |
dc.contributor.nonIdAuthor | 박정민 | - |
dc.contributor.nonIdAuthor | 김경재 | - |
dc.subject.keywordAuthor | Support Vector Machine | - |
dc.subject.keywordAuthor | Bankruptcy Prediction | - |
dc.subject.keywordAuthor | Artificial Neural Network | - |
dc.subject.keywordAuthor | Logistic Regression | - |
dc.subject.keywordAuthor | Multivariate Discriminant Analysis | - |
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