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ArticleClassifiers selection in ensembles using genetic algorithms for bankruptcy prediction

Myoung-Jong Kim2012

Article2012

Classifiers selection in ensembles using genetic algorithms for bankruptcy prediction

Myoung-Jong Kim · Dae-Ki Kang

87 citations·0/0 files stored·Expert Systems with Applications

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Financial Distress and Bankruptcy Prediction Evolutionary Algorithms and Applications Imbalanced Data Classification Techniques

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models 1977ZETATM analysis A new model to identify bankruptcy risk of corporations 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review 1990A neural network model for bankruptcy prediction 2004An application of support vector machines in bankruptcy prediction model 1996A survey of business failures with an emphasis on prediction methods and industrial applications

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2014Optimizing parameters of support vector machine using fast messy genetic algorithm for dispute classification 2019Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends 2018Failure pattern-based ensembles applied to bankruptcy forecasting 2020Performance assessment of ensemble learning systems in financial data classification 2019Forecasting bankruptcy using biclustering and neural network-based ensembles

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Year2012

Typearticle

Published2012-02-17

VenueExpert Systems with Applications

ISSN-L0957-4174

Languageen

Citations87

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1016/j.eswa.2012.02.072

openalex_workW2064528384

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2021Dynamic self-organizing feature map-based models applied to bankruptcy prediction