Abstract

Small and medium-sized logistics companies are playing an increasingly important part in social life. We
selected the data of small and medium-sized logistical companies in Beijing, Shanghai and Guangzhou,
reformulated ordinal regression support vector machine method so that different input points could make
different contributions to decide hyper plane, to analyze multi-classification of credit rating problem, and divided
them into four different categories to demonstrate the good performance. The effectiveness of this improved
method is verified in multi-classification of credit rating of small and medium-sized logistical companies and the
results show that our method is promising and can be used to other multi-classification problems. 

 

 

 

 

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