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About: Maximum entropy probability distribution     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : yago:WikicatDiscreteDistributions, within Data Space : dbpedia.demo.openlinksw.com associated with source document(s)

Type: yago:WikicatContinuousDistributionsyago:Abstraction100002137yago:Arrangement105726596yago:Cognition100023271yago:Distribution105729036yago:PsychologicalFeature100023100yago:Structure105726345yago:WikicatDiscreteDistributions New Facet based on Instances of this Class

In statistics and information theory, a maximum entropy probability distribution has entropy that is at least as great as that of all other members of a specified class of probability distributions. According to the principle of maximum entropy, if nothing is known about a distribution except that it belongs to a certain class (usually defined in terms of specified properties or measures), then the distribution with the largest entropy should be chosen as the least-informative default. The motivation is twofold: first, maximizing entropy minimizes the amount of prior information built into the distribution; second, many physical systems tend to move towards maximal entropy configurations over time.