1993/03/01 by R. G. Cowell, A. P. Dawid, David J. Spiegelhalter · 2 citations
Computer Science · #Bayesian Modeling and Causal Inference #AI-based Problem Solving and Planning #Data Mining Algorithms and Applications
paper · doi:10.1109/34.204903
openalex publication_date 1993/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
Probabilistic expert systems based on Bayesian networks require initial specification of both qualitative graphical structure and quantitative conditional probability assessments. As (possibly incomplete) data accumulate on real cases, the parameters of the system may adapt, but it is also essential that the initial specifications be monitored with respect to their predictive performance. A range of monitors based on standardized scoring rules that are designed to detect both qualitative and quantitative departures from the specified model is presented. A simulation study demonstrates the efficacy of these monitors at uncovering such departures.>