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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Bibliographic Details
Main Authors: Maria R. Lentini, Umashanger Thayasivam
Format: Article
Language:English
Published: SpringerOpen 2025-03-01
Series:Journal of Big Data
Online Access:https://doi.org/10.1186/s40537-024-01036-y
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