Conditional probability is the probability of a random variable when some other random variable is given. Quick Probability Reviewīefore continue, to refresh our memories let me give you the definition of conditional property. Similarly, these causality relations can be constructed for other problems and inference techniques can be applied to interesting results. With given symptoms and their resulting disease, we construct our Belief Network and when a new patient comes, we can infer which disease or diseases may have the new patient by providing probabilities for each disease. To clarify this, let’s consider a disease diagnosis problem. The main objective of these networks is trying to understand the structure of causality relations. For example, disease diagnosis, optimized web search, spam filtering, gene regulatory networks, etc. What do we use the Bayesian Networks for?īayesian Networks are applied in many fields. In addition, I will show you an example implementation of this kind of network.

Today, I will try to explain the main aspects of Belief Networks, especially for applications which may be related to Social Network Analysis(SNA).

An Example Bayesian Belief Network Representation

Symptom network analysis definition