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Conditional entropy

In information theory, the conditional entropy quantifies the amount of information needed to describe the outcome of a random variable Y {\displaystyle Y} given that the value of another random variable X {\displaystyle X} is known. Here, information is measured in shannons, nats, or hartleys. The "entropy of Y {\displaystyle Y} conditioned on X…

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Conditional differential entropy

Generalization to quantum theory

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Conditional entropy

Nodes36
Edges35
Triples18
Avg. degree1.94
Density0.055556
Components1

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Conditional entropy

Top relations

related to Chain rule · 5
Conditional entropy → Assume, Now, Once, The, This
related to Bayes' rule · 4
Conditional entropy → Bayes, Proof, Subtracting, Symmetry
related to Motivation · 3
Conditional entropy → Denote, Let, The
related to Definition · 2
Conditional entropy → Let, The
related to Generalization to quantum theory · 2
Conditional entropy → In, The
related to Properties · 2
Conditional entropy → As, In

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Important terminology

displaystyle entropy conditional mathrm information random value variables given theory discrete definition rule differential defined describe variable independent quantum estimator

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Conditional entropyrelated to Bayes' ruleBayes0.60section
Conditional entropyrelated to Bayes' ruleProof0.60section
Conditional entropyrelated to Bayes' ruleSymmetry0.60section
Conditional entropyrelated to Bayes' ruleSubtracting0.60section
Conditional entropyrelated to Chain ruleAssume0.60section
Conditional entropyrelated to Chain ruleNow0.60section
Conditional entropyrelated to Chain ruleOnce0.60section
Conditional entropyrelated to Chain ruleThis0.60section
Conditional entropyrelated to Chain ruleThe0.60section
Conditional entropyrelated to DefinitionThe0.60section
Conditional entropyrelated to DefinitionLet0.60section
Conditional entropyrelated to Generalization to quantum theoryIn0.60section

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