Fuzzy classification method in credit risk

Authors:
Hossein Yazdani;Halina Kwasnicka
Affiliations:
Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland;Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland
Venue:
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
Year:
2012

Citing 5
Cited 0

Credit Risk Assessment Using Statistical and MachineLearning: Basic Methodology and Risk Modeling Applications

Computational Economics - Computational Studies at Stanford
Learning fuzzy classification rules from labeled data

Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques
Top 10 algorithms in data mining

Knowledge and Information Systems
Clustering

Clustering

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper presents FCMCR a fuzzy classification method for credit risk in banking system. Our implementation makes use of fuzzy rules to evaluate similarity between objects as well as using membership degree for features respect to each class. The method is inspired by Fuzzy classification method and was tested using loan data from a large bank. Our result shows that the proposed method is competitive with other approaches reported in the literature.