Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy
- 30 June 2010
- journal article
- Published by Elsevier BV in Neurocomputing
- Vol. 73 (10-12), 2047-2060
- https://doi.org/10.1016/j.neucom.2009.11.034
Abstract
No abstract availableKeywords
This publication has 58 references indexed in Scilit:
- Hybrid genetic algorithms and support vector machines for bankruptcy predictionExpert Systems with Applications, 2006
- A hybrid genetic model for the prediction of corporate failureComputational Management Science, 2004
- Improving Decision Effectiveness of Artificial Neural Networks: A Modified Genetic Algorithm ApproachDecision Sciences, 2003
- Bankruptcy prediction for credit risk using neural networks: A survey and new resultsIEEE Transactions on Neural Networks, 2001
- Comparative analysis of failure prediction methods: the Finnish caseEuropean Accounting Review, 1999
- Predicting bankruptcies with the self-organizing mapNeurocomputing, 1998
- An empirical comparison of bankruptcy modelsThe Financial Review, 1998
- Feedforward neural networks in the classification of financial informationThe European Journal of Finance, 1997
- Using Machine Learning, Neural Networks, and Statistics to Predict Corporate BankruptcyComputer-Aided Civil and Infrastructure Engineering, 1997
- Neural network prediction analysis: The bankruptcy caseNeurocomputing, 1996