Research Article
Toward an Efficient and Effective Credit Scorer for Cross-Border E-Commerce Enterprises
Table 1
WOE for the “average age of the customers.” The values are binned using equal-frequency clustering and then normalized.
| Bin | WOE |
| 1: [0, 0.0028] | −1.4633 | 2: [0.0028, 0.0061] | −0.639 | 3: [0.0061, 0.0082] | −0.4933 | 4: [0.0082, 0.0149] | 0.0276 | 5: [0.0149, 0.0215] | 0.5489 | 6: [0.0215, 0.048] | 0.5802 | 7: [0.048, 0.0607] | 0.8021 | 8: [0.0607, 1] | 0.9527 |
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