= Fano's inequality
{wiki=Fano's_inequality}
Fano's inequality is a result in information theory that provides a lower bound on the probability of error in estimating a message based on observed data. It quantifies the relationship between the uncertainty of a random variable and the minimal probability of making an incorrect estimation of that variable when provided with some information. More formally, consider a random variable \\( X \\) with \\( n \\) possible outcomes and another random variable \\( Y \\), which represents the "guess" or estimation of \\( X \\).
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