**Maximum entropy** may refer to:

- The principle of maximum entropy
- The maximum entropy probability distribution
- Maximum entropy spectral estimation
- Maximum entropy spectral analysis
- Maximum entropy thermodynamics
- The law of maximum entropy production
- Entropy maximization
- Maximum entropy classifier

### Other articles related to "maximum entropy, maximum, entropy":

**Maximum Entropy**Spectral Analysis

...

**Maximum entropy**spectral analysis (MaxEnt spectral analysis) is a method of improving spectral quality based on the principle of

**maximum entropy**... It is simply the application of

**maximum entropy**modeling to any type of spectrum and is used in all fields where data is presented in spectral form ... In

**maximum entropy**modeling probability distributions are created on the basis of that which is known, and leads to a type of statistical inference about the missing information which is called the

**maximum**...

Max Ent - Applications - Prior Probabilities

... The principle of

... The principle of

**maximum entropy**is often used to obtain prior probability distributions for Bayesian inference ... Jaynes was a strong advocate of this approach, claiming the**maximum entropy**distribution represented the least informative distribution ... A large amount of literature is now dedicated to the elicitation of**maximum entropy**priors and links with channel coding ...Max Ent - Testable Information

... The principle of

... The principle of

**maximum entropy**is useful explicitly only when applied to testable information ... Given testable information, the**maximum entropy**procedure consists of seeking the probability distribution which maximizes information**entropy**, subject to the constraints of the information ...**Entropy**maximization with no testable information takes place under a single constraint the sum of the probabilities must be one ...Uninformative Priors

... Jaynes, is to use the principle of

... Jaynes, is to use the principle of

**maximum entropy**(MAXENT) ... The motivation is that the Shannon**entropy**of a probability distribution measures the amount of information contained in the distribution ... The larger the**entropy**, the less information is provided by the distribution ...### Famous quotes containing the words entropy and/or maximum:

“Just as the constant increase of *entropy* is the basic law of the universe, so it is the basic law of life to be ever more highly structured and to struggle against *entropy*.”

—Václav Havel (b. 1936)

“Probably the only place where a man can feel really secure is in a *maximum* security prison, except for the imminent threat of release.”

—Germaine Greer (b. 1939)

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