Application of support vector machines on the basis of the first Hungarian bankruptcy model
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- Nyitrai, Tamás, 2014.
"Növelhető-e a csőd-előrejelző modellek előre jelző képessége az új klasszifikációs módszerek nélkül?
[Can the predictive capacity of bankruptcy forecasting models be increased without new classific," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 566-585.
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Keywordsbankruptcy prediction; classification; data preparation; outliers; support vector machines (SVM); ROC curve analysis;
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
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