credit risk evaluation has played an extremely important role in the credit
risk management of commercial banks. Firstly, through Logistic regression, this
paper selects and determines the clustering factors. Then the bilateral
clustering structure is proposed. Based on the clustering structure, we cluster
to the test samples, and distinguish the individual credit risk as well.
Finally, we use the ROC method to test the proposed model and Logistic regression
model. The results of comparison show that the discrimination method of
individual credit risk based on bilateral clustering can better identify the
Cite this paper
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