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Kullback–Leibler divergence and Total correlation

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Kullback–Leibler divergence and Total correlation

Kullback–Leibler divergence vs. Total correlation

In mathematical statistics, the Kullback–Leibler divergence (also called relative entropy) is a measure of how one probability distribution diverges from a second, expected probability distribution. In probability theory and in particular in information theory, total correlation (Watanabe 1960) is one of several generalizations of the mutual information.

Similarities between Kullback–Leibler divergence and Total correlation

Kullback–Leibler divergence and Total correlation have 3 things in common (in Unionpedia): Bit, Entropy (information theory), Mutual information.

Bit

The bit (a portmanteau of binary digit) is a basic unit of information used in computing and digital communications.

Bit and Kullback–Leibler divergence · Bit and Total correlation · See more »

Entropy (information theory)

Information entropy is the average rate at which information is produced by a stochastic source of data.

Entropy (information theory) and Kullback–Leibler divergence · Entropy (information theory) and Total correlation · See more »

Mutual information

In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two variables.

Kullback–Leibler divergence and Mutual information · Mutual information and Total correlation · See more »

The list above answers the following questions

Kullback–Leibler divergence and Total correlation Comparison

Kullback–Leibler divergence has 123 relations, while Total correlation has 13. As they have in common 3, the Jaccard index is 2.21% = 3 / (123 + 13).

References

This article shows the relationship between Kullback–Leibler divergence and Total correlation. To access each article from which the information was extracted, please visit:

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