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In information theory, joint entropy is a measure of the uncertainty associated with a set of variables.
Definition, Properties & Relations to other entropy measures
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entropy joint variables displaystyle random set definition differential two continuous individual entropies equal discrete defined information sum values probability log
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Joint entropy | is a | measure of the uncertainty associated with a set of variables | 0.90 | text |
| Joint entropy | related to Definition | The | 0.60 | section |
| Joint entropy | related to Definition | Let | 0.60 | section |
| Joint entropy | related to Definition | For | 0.60 | section |
| Joint entropy | related to Greater than individual entropies | The | 0.60 | section |
| Joint entropy | related to Less than or equal to the sum of individual entropies | The | 0.60 | section |
| Joint entropy | related to Less than or equal to the sum of individual entropies | This | 0.60 | section |
| Joint entropy | related to Nonnegativity | The | 0.60 | section |
| Joint entropy | related to Relations to other entropy measures | Joint | 0.60 | section |
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