Conditional entropy
Measure of relative information in probability theory
Conditional entropy
In information theory, the conditional entropy quantifies the amount of information needed to describe the outcome of a random variable Y {\displaystyle Y} given that the value of another random variable X {\displaystyle X} is known. Here, information is measured in shannons, nats, or hartleys. The "entropy of Y {\displaystyle Y} conditioned on X {\displaystyle X} " is denoted as H ( Y | X ) {\displaystyle \mathrm {H} (Y|X)} .
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