Applied multivariate statistical analysis
Applied multivariate statistical analysis
The nature of statistical learning theory
The nature of statistical learning theory
Practical genetic algorithms
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Selecting Bankruptcy Predictors Using a Support Vector Machine Approach
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
Expert Systems with Applications: An International Journal
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This research proposes a diagnosis model for business crisis integrated a real-valued genetic algorithm and support vector machine. A series of learning and testing processes with real business data show that the diagnosis model has a crisis prediction accuracy of up to 95.56%, demonstrating the applicability of the proposed method. Six features, including five financial and one intellectual capital indices, are used for the diagnosis. These features are common and easily accessible from publicly available information. The proposed GA-SVM diagnosis model can be used by firms for self-diagnosis and evaluation.