Value-at-risk student prescription trees for price personalization
Abstract Value-at-risk (VaR) models use statistical techniques to estimate potential losses in financial portfolios over a specified time period. In contrast, student prescription trees (SPTs) are interpretable policy optimizers that estimate individual consumer demand and utilize decision trees to...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-03-01
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| Series: | Journal of Big Data |
| Online Access: | https://doi.org/10.1186/s40537-024-01036-y |
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