Research Article
Research on Efficiency in Credit Risk Prediction Using Logistic-SBM Model
Table 2
Feature information table.
| No. | Features | Feature interpretation | Class number |
| 1 | DEA_score | Efficiency score of borrowing | 5 | 2 | Education | Borrower’s highest education | 5 | 3 | Marriage | Marital status of the borrower | 4 | 4 | Home type | Type of residence of the borrower | 4 | 5 | Company | Type of work unit of the borrower | 5 | 6 | Pay method | How the borrower pays wages | 3 | 7 | Job type | Job type of the borrower | 4 | 8 | Product name | Types of borrowers’ lending products | 4 | 9 | Sales department | Which business department is responsible for the borrower’s lending behavior | 3 | 10 | Bank | Ownership of bank card signed by the borrower | 5 | 11 | Family aware | Is the borrower aware of his borrowing behavior | 3 | 12 | Pro_id | The registered residence of a borrower | 5 | 13 | Birth month | Month of birth of the borrower | 3 | 14 | Birthday | Date of birth of the borrower | 4 | 15 | Inapv_edr | External debt ratio of borrowers | 5 | 16 | Inapv_idr | Internal debt ratio of the borrower | 5 | 17 | Inapv_tdr | Total debt ratio of the borrower | 5 | 18 | Age | Age of borrower | 6 | 19 | Entry date | Working days of the borrower | 5 |
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