Assessing Skip-Tracing Information in Repossession Prediction Using Ensemble Learning and SHAP Analysis
Predictive modeling for auto-repossession risk has received little academic attention despite its operational importance. When a vehicle cannot be located, repossession companies often rely on skip-tracing, an established industry practice that uses third-party data sources such as license plate rec...
Збережено в:
| Автори: | , , |
|---|---|
| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
IEEE
2026-01-01
|
| Серія: | IEEE Access |
| Предмети: | |
| Онлайн доступ: | https://ieeexplore.ieee.org/document/11589248/ |
| Теги: |
Немає тегів, Будьте першим, хто поставить тег для цього запису!
|