Conditional entropy

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