Neural network credit scoring models
Computers and Operations Research - Neural networks in business
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Rough Sets: Theoretical Aspects of Reasoning about Data
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Computers and Operations Research
Credit scoring with a data mining approach based on support vector machines
Expert Systems with Applications: An International Journal
A Comparison Study of Credit Scoring Models
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 01
Constructing a reassigning credit scoring model
Expert Systems with Applications: An International Journal
Credit scoring algorithm based on link analysis ranking with support vector machine
Expert Systems with Applications: An International Journal
A Hybrid Credit Scoring Model Based on Genetic Programming and Support Vector Machines
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 07
A new two-stage hybrid approach of credit risk in banking industry
Expert Systems with Applications: An International Journal
Genetic programming for credit scoring: The case of Egyptian public sector banks
Expert Systems with Applications: An International Journal
Building credit scoring models using genetic programming
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hybrid mining approach in the design of credit scoring models
Expert Systems with Applications: An International Journal
A new credit scoring method based on rough sets and decision tree
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
An application of locally linear model tree algorithm for predictive accuracy of credit scoring
MEDI'11 Proceedings of the First international conference on Model and data engineering
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Artificial Intelligence Review
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Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
In recent years, more and more people, especially young people, begin to use credit card with the changing of consumption concept in China so that the business on credit cards is growing fast. Therefore, it is significative that some effective tools such as credit-scoring models are created to help those decision makers engaged in credit cards. A novel credit-scoring model, called vertical bagging decision trees model (abbreviated to VBDTM), is proposed for the purpose in this paper. The model is a new bagging method that is different from the traditional bagging. The VBDTM model gets an aggregation of classifiers by means of the combination of predictive attributes. In the VBDTM model, all train samples and just parts of attributes take part in learning of every classifier. By contrast, classifiers are trained with the sample subsets in the traditional bagging method and every classifier has the same attributes. The VBDTM has been tested by two credit databases from the UCI Machine Learning Repository, and the analysis results show that the performance of the method proposed by us is outstanding on the prediction accuracy.