Evaluating the Weighted Sum Algorithm for Estimating Conditional Probabilities in Bayesian Networks.

Abstract

A Bayesian Network (BN) is a probabilistic modelling technique that allows for reasoning under uncertainty. BNs have been applied in many areas including: forecasting, estimation, classification, recognition, and inference. A BN consists of two components: The first is a Direct Acyclic Graph (DAG) that represents factors of interest (as nodes) and associated causal relations (as edges). For example, Figure 1 shows a naive BN for forecasting the rate of growth for a hypothetical plant, given the amount of sunlight and water it receives.

Publication
Proceedings of SEKE 2010