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
Credit scoring with a data mining approach based on support vector machines
Expert Systems with Applications: An International Journal
Using neural network ensembles for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
Support vector machines for credit scoring and discovery of significant features
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
Building credit scoring models using genetic programming
Expert Systems with Applications: An International Journal
Hybrid mining approach in the design of credit scoring models
Expert Systems with Applications: An International Journal
Credit risk evaluation with least square support vector machine
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Comments on “Dynamical Optimal Training for Interval Type-2 Fuzzy Neural Network (T2FNN)”
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new fuzzy support vector machine to evaluate credit risk
IEEE Transactions on Fuzzy Systems
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Credit scoring is regarded as a core assessment tool of Lenders during the last few decades and has been widely studied in the areas of statistics, and artificial intelligence. Nowadays credit risk appraisal is an area of renewed interest due to recent financial crises. Many novel approaches have been proposed to increase the accuracy of credit scoring. In this paper, a Fuzzy Type 2 Inference System (FT2IS) is proposed to deal with the credit scoring problem.