Mutual Information

Mutual Information is a measure from information theory that quantifies how much knowing one thing reduces uncertainty about another. Essentially, it reflects the amount of shared information between two variables. If two variables are highly related, knowing one significantly reduces the uncertainty about the other, resulting in high mutual information. Conversely, if they are independent, knowing one provides no insight into the other, and mutual information is low or zero. It’s a way to understand the strength of the relationship between variables in terms of information content, applicable in fields like data analysis, machine learning, and communication systems.