Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Support Vector Machines for 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Self-Organizing Maps
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
An SVM-based Algorithm for Identification of Photosynthesis-specific Genome Features
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Editorial: special issue on learning from imbalanced data sets
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
Does cost-sensitive learning beat sampling for classifying rare classes?
UBDM '05 Proceedings of the 1st international workshop on Utility-based data mining
Training Cost-Sensitive Neural Networks with Methods Addressing the Class Imbalance Problem
IEEE Transactions on Knowledge and Data Engineering
Credit scoring with a data mining approach based on support vector machines
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A distributed PSO-SVM hybrid system with feature selection and parameter optimization
Applied Soft Computing
A binary classification method for bankruptcy prediction
Expert Systems with Applications: An International Journal
Multiple classifier application to credit risk assessment
Expert Systems with Applications: An International Journal
Building credit scoring models using genetic programming
Expert Systems with Applications: An International Journal
Using partial least squares and support vector machines for bankruptcy prediction
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
This study proposes a novel PSO---CS-SVM model that hybridizes the particle swarm optimization (PSO) and cost sensitive support vector machine (CS-SVM) to deal with the problem of unbalanced data classification and asymmetry misclassification cost in loan default discrimination problem. Cost sensitive learning is applied to the standard SVM by integrating misclassification cost of each sample into standard SVM and PSO is employed for parameter determination of the CS-SVM. Meantime, the financial data are discretized by using the self-organizing mapping neural network. And the evaluation indices are reduced without information loss by genetic algorithm for decreasing the complexity of the model. The effectiveness of integrated model of CS-SVM and PSO is verified by three experiments comparing with traditional CS-SVM, PSO---SVM, SVM and BP neural network through real loan default data of companies in China. The corresponding results indicate that the accuracy rate, hit rate, covering rate and lift coefficient are improved dramatically by the developed approach. The proposed method can control the different types of errors distribution with various cost of misclassification accurately, reduce the total misclassification cost largely, and distinguish the loan default problems effectively.