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Reference.org
Conditional entropy
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<p>In <a href="/facts/Information_theory/qNLH3U5P">information theory</a>, the conditional entropy quantifies the amount of information needed to describe the outcome of a <a href="/facts/Random_variable/TwTBXnLT">random variable</a> Y {\displaystyle Y} given that the value of another random variable X {\displaystyle X} is known. Here, information is measured in <a href="/facts/Shannon_(unit)/VEevYzKM">shannons</a>, <a href="/facts/Nat_(unit)/UgNgfVgI">nats</a>, or <a href="/facts/Hartley_(unit)/HHnoxYMR">hartleys</a>. The <i>entropy of Y {\displaystyle Y} conditioned on X {\displaystyle X} </i> is written as H ( Y | X ) {\displaystyle \mathrm {H} (Y|X)} . </p>