The Venn Diagram below illustrates this concept:
Hence, the Conditional Entropy is a key element in defining the Mutual Information between
is equivalent to:
and furthermore equivalent to:
This allows computing the Mutual Information between any two variables.
For a given network, BayesiaLab can report the Mutual Information in several contexts:
Main Menu > Analysis > Report > Target > Relationship with Target Node.
- Note that this table shows the Mutual Information of each node, e.g., XRay, Dyspnea, etc., only with regard to the Target Node, Cancer.
Main Menu > Analysis > Report > Relationship Analysis:
- The Mutual Information can also be shown by selecting
Main Menu > Analysis > Visual > Overall > Arc > Mutual Informationand then clicking the Show Arc Comments iconor selecting
Main Menu > View > Show Arc Comments.
- Note that the corresponding options under
Preferences > Analysis > Visual Analysis > Arc's Mutual Information Analysishave to be selected first:
- In Preferences, Child refers to the Relative Mutual Information from the Parent onto the Child node, i.e., in the direction of the arc.
- Conversely, Parent refers to the Relative Mutual Information from the Child onto the Parent node, i.e., in the opposite direction of the arc.