Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
C4.5: programs for machine learning
C4.5: programs for machine learning
Neural network credit scoring models
Computers and Operations Research - Neural networks in business
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm
Genetic Programming and Evolvable Machines
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
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Credit scoring with a data mining approach based on support vector machines
Expert Systems with Applications: An International Journal
Application areas of AIS: The past, the present and the future
Applied Soft Computing
Immunological Computation: Theory and Applications
Immunological Computation: Theory and Applications
Computational Intelligence: An Introduction
Computational Intelligence: An Introduction
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Credit rating by hybrid machine learning techniques
Applied Soft Computing
Review Article: Recent Advances in Artificial Immune Systems: Models and Applications
Applied Soft Computing
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Generating Compact Classifier Systems Using a Simple Artificial Immune System
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Credit rating using a hybrid voting ensemble
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
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The primary concern of the rating policies for a banking industry is to develop a more objective, accurate and competitive scoring model to avoid losses from potential bad debt. This study proposes an artificial immune classifier based on the artificial immune network (named AINE-based classifier) to evaluate the applicants' credit scores. Two experimental credit datasets are used to show the accuracy rate of the artificial immune classifier. The ten-fold cross-validation method is applied to evaluate the performance of the classifier. The classifier is compared with other data mining techniques. Experimental results show that for the AINE-based classifier in credit scoring is more competitive than the SVM and hybrid SVM-based classifiers, except the BPN classifier. We further compare our classifier with other three AIS-based classifiers in the benchmark datasets, and show that the AINE-based classifier can rival the AIRS-based classifiers and outperforms the SAIS classifier when the number of attributes and classes increase. Our classifier can provide the credit card issuer with accurate and valuable information of credit scoring analyses to avoid making incorrect decisions that result in the loss of applicants' bad debt.