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Conditional entropy is the difference between the joint entropy of X and Y and the marginal entropy of Y. This relationship is expressed by the entropy chain rule: H(X|Y) = $H(X,Y) - H(Y)$.

Conditions: X and Y are discrete random variables with well-defined joint and marginal entropies.

Conditional entropy is the difference between the joint entropy of X and Y and the marginal entropy of Y. This relationship is expressed by the entropy chain rule: H(X|Y) = $H(X,Y) - H(Y)$.

Conditions: X and Y are discrete random variables with well-defined joint and marginal entropies.