New Feature: Expected Log-Loss
One of the key metric in Information Theory is Entropy:
The entropy is thus the sum the Expected Log-Loss of each state of variable when using network ;
As of version 7.0, you can now select to get the Expected Log-Loss of the states in the monitors instead of their probabilities.
This insteresting example shows that setting Bronchitis = Yes reduces the Entropy of Dyspnea, without changing the Expected Log-Loss of Dyspnea = False.
Indeed, below are curves that show how the entropy is decomposed for a binary variable; this confirm that the Expected Log-Loss is similar for probabilities equal to 0.19 and 0.57.
The Expected Log-Losses are now also available int the tooltip associated with the monitors, in the Information Mode , while hovering over the monitor: