Research Article
One-Step Dynamic Classifier Ensemble Model for Customer Value Segmentation with Missing Values
Table 1
Attribute description of “China churn” dataset.
| Attribute | Name | Missing rate (%) |
| | Total consumption times | 7.37 | | Total consumption amount | 6.76 | | Total cash times | 4.95 | | Customer survival time | 8.63 | | Total contributions | 11.12 | | Valid survival time | 8.05 | | Average amount ratio | 10.75 | | Whether associated charge | 12.18 | | Consumption times in the last 1 month | 2.09 | | Consumption times in the last 2 months | 3.13 | | Consumption times in the last 3 months | 8.08 | | Consumption times in the last 4 months | 9.31 | | Consumption times in the last 5 months | 3.87 | | Cash times in the last 1 month | 5.07 | | Cash times in the last 2 months | 7.04 | | Cash times in the last 3 months | 8.97 | | Cash times in the last 6 months | 10.60 | | Months of transaction times reducing continuously | 8.48 | | If overdue in the last 1 month | 7.80 | | If overdue in the last 2 months | 13.76 | | Amount usage ratio in the last 1 month/historical average usage ratio | 6.11 | | Sex | 2.70 | | Annual income | 14.84 | | Nature of work industry | 11.18 | | Education | 8.63 |
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