Computer
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International Journal of Electronic Finance
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International Journal of Electronic Finance
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International Journal of Electronic Finance
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International Journal of Electronic Finance
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International Journal of Electronic Finance
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International Journal of Electronic Finance
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International Journal of Electronic Finance
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ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
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International Journal of Electronic Finance
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CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Explaining investors' reaction to internet security breach using deterrence theory
International Journal of Electronic Finance
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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.