A genetic-based hybrid approach to corporate failure prediction
This paper proposes a genetic-based hybrid approach to predict the possibility of corporate failure. We use Genetic Algorithm (GA) to select the critical variables set and optimise the weight of each classifier for integrating the best features of several classification approaches (such as discriminant analysis, logistic regression and neural networks) in order to enhance prediction results. GA with nonlinear searching capabilities extracts more critical feature variables if compared with the Stepwise Method. This means that the undesirable variables for classification models will be cleaned out by GA. In addition, our experimental results show that this hybrid approach obtains better prediction performance than when using a single approach effectively.
Volume (Year): 2 (2008)
Issue (Month): 2 ()
|Contact details of provider:|| Web page: http://www.inderscience.com/browse/index.php?journalID=171|
When requesting a correction, please mention this item's handle: RePEc:ids:ijelfi:v:2:y:2008:i:2:p:241-255. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Graham Langley)
If references are entirely missing, you can add them using this form.