Probabilistic graphical models such as Bayesian networks are widely used for large-scale data analysis in various fields such as customer data analysis and medical diagnosis, as they model probabilistic knowledge naturally and allow the use of efficient inference algorithms to draw conclusions from the model. Sensitivity analysis of probabilistic graphical models is the analysis of the relationships between the inputs (local beliefs), such as network parameters, and the outputs (global beliefs), such as values of probabilistic queries, and addresses the central research problem of...
Probabilistic graphical models such as Bayesian networks are widely used for large-scale data analysis in various fields such as customer da...