Research on Multi-Classification of Credit Rating of Small and Medium-Sized Enterprises in Growth Enterprises Board Based on Fuzzy Ordinal Regression Support Vector Machine

Ying CHEN

Abstract


It is necessary to classify credit rating of small and medium-sized companies in Chinese growth enterprises board. We selected the data of 90 small and medium-sized companies, used fuzzy theory to calculate the qualitative variables, and reformulated support vector machine for ordinal regression method so that different input points can make different contributions to decide hyper plane, to analyze multi-classification of credit rating problem, and divided them into four different categories and demonstrated the good performance. The effectiveness of this improved method is verified in multi-classification of credit rating of small and medium-sized logistical companies; the experiment results show that our method is promising and can be used to other multi-classification problems.


Full Text: PDF DOI: 10.5539/ijef.v4n3p248

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International Journal of Economics and Finance  ISSN  1916-971X (Print) ISSN  1916-9728 (Online)

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