Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Determining the saliency of input variables in neural network classifiers
Computers and Operations Research
Using neural networks for data mining
Future Generation Computer Systems - Special double issue on data mining
Fuzzy Sets and Systems
Neural network credit scoring models
Computers and Operations Research - Neural networks in business
Rough set theory applied to (fuzzy) ideal theory
Fuzzy Sets and Systems
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
A comparative study of fuzzy rough sets
Fuzzy Sets and Systems
A methodology to explain neural network classification
Neural Networks
Symbolic and numerical regression: experiments and applications
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
Genetic programming in classifying large-scale data: an ensemble method
Information Sciences: an International Journal - Special issue: Soft computing data mining
Journal of Management Information Systems - Special section: Data mining
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
Neural nets versus conventional techniques in credit scoring in Egyptian banking
Expert Systems with Applications: An International Journal
A distributed PSO-SVM hybrid system with feature selection and parameter optimization
Applied Soft Computing
AN IMPROVED KNOWLEDGE-ACQUISITION STRATEGY BASED ON GENETIC PROGRAMMING
Cybernetics and Systems
CASE-BASED REASONING FOR PREDICTING MULTIPERIOD FINANCIAL PERFORMANCES OF TECHNOLOGY-BASED SMEs
Applied Artificial Intelligence
An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
Expert Systems with Applications: An International Journal
Constructing a reassigning credit scoring model
Expert Systems with Applications: An International Journal
The individual borrowers recognition: Single and ensemble trees
Expert Systems with Applications: An International Journal
Feature selection in bankruptcy prediction
Knowledge-Based Systems
The consumer loan default predicting model - An application of DEA-DA and neural network
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
Exploring high-performers' required competencies
Expert Systems with Applications: An International Journal
Development of a quick credibility scoring decision support system using fuzzy TOPSIS
Expert Systems with Applications: An International Journal
Credit rating by hybrid machine learning techniques
Applied Soft Computing
Multiple classifier application to credit risk assessment
Expert Systems with Applications: An International Journal
Combination of feature selection approaches with SVM in credit scoring
Expert Systems with Applications: An International Journal
Credit rating method with heterogeneous information
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
The hybrid credit scoring model based on KNN classifier
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Vertical bagging decision trees model for credit scoring
Expert Systems with Applications: An International Journal
A data mining framework for detecting subscription fraud in telecommunication
Engineering Applications of Artificial Intelligence
Learning without default: a study of one-class classification and the low-default portfolio problem
AICS'09 Proceedings of the 20th Irish conference on Artificial intelligence and cognitive science
A hybrid model for credit evaluation problem
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
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
Two layered Genetic Programming for mixed-attribute data classification
Applied Soft Computing
Decision tree-based technology credit scoring for start-up firms: Korean case
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy type 2 inference system for credit scoring
ACMOS'09 Proceedings of the 11th WSEAS international conference on Automatic control, modelling and simulation
Exploring the behaviour of base classifiers in credit scoring ensembles
Expert Systems with Applications: An International Journal
Efficient and effective classification of creditworthiness using ant colony optimization
Proceedings of the 50th Annual Southeast Regional Conference
Determinants of intangible assets value: The data mining approach
Knowledge-Based Systems
Two-level classifier ensembles for credit risk assessment
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A personalized trustworthy seller recommendation in an open market
Expert Systems with Applications: An International Journal
Assessing scorecard performance: A literature review and classification
Expert Systems with Applications: An International Journal
A loan default discrimination model using cost-sensitive support vector machine improved by PSO
Information Technology and Management
Hi-index | 12.09 |
Credit scoring models have been widely studied in the areas of statistics, machine learning, and artificial intelligence (AI). Many novel approaches such as artificial neural networks (ANNs), rough sets, or decision trees have been proposed to increase the accuracy of credit scoring models. Since an improvement in accuracy of a fraction of a percent might translate into significant savings, a more sophisticated model should be proposed to significantly improving the accuracy of the credit scoring mode. In this paper, genetic programming (GP) is used to build credit scoring models. Two numerical examples will be employed here to compare the error rate to other credit scoring models including the ANN, decision trees, rough sets, and logistic regression. On the basis of the results, we can conclude that GP can provide better performance than other models.