Variation of Information (VI) is a measure of the distance between two probability distributions. It is particularly used in information theory and statistics to quantify the amount of information that one distribution shares with another. This concept can be useful in various contexts, including clustering, classification, and comparing the outputs of algorithms. The Variation of Information between two random variables (or distributions) \( X \) and \( Y \) is defined in terms of their entropy and mutual information.
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