Mathematics for AI and Machine Learning

Foundations for modern AI and machine learning

Mutual Information

Chapter 14 Probability & information

Chapter 14: Information Theory — Mutual Information

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Mutual Information — high-resolution mind-map icon

From the book

Chapter 14: Information Theory. In the chapter mind map this icon labels Mutual Information: $I(X;Y)$. The discussion below is excerpted and lightly edited from § Definition: Mutual Information in Mathematics for AI and Machine Learning.

For two random variables $X$ and $Y$ with joint distribution $p(x, y)$ and marginals $p(x)$ and $p(y)$, the mutual information is

For continuous random variables, replace sums with integrals.

What this drawing shows

What you see. Represents shared information between random variables.

In the mind map. Chapter 14 — Mutual Information. See From the book above for definitions, figures, and worked examples.

Where to read next

Open Chapter 14 companion →

Read the full definitions, figures, and worked examples in Chapter 14: Information Theory — see the mind-map node Mutual Information.