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Probabilistic reasoning and probabilistic neural networks

✍ Scribed by Gerhard Pass

Publisher
John Wiley and Sons
Year
1992
Tongue
English
Weight
642 KB
Volume
7
Category
Article
ISSN
0884-8173

No coin nor oath required. For personal study only.

✦ Synopsis

The Boltzmann machine is a probabilistic neural network describing the associative dependency of variables. It yields a probability distribution, which is a special case of the distribution generated by probabilistic inference networks. Hence both types of networks can be combined allowing to integrate probabilistic rules as well as unspecified associations in a sound way. The resulting network may have a number of interesting features including cycles of probabilistic rules, and hidden "unobservable" variables. The maximum likelihood approach is used to combine possibly conflicting pieces of information on rules or associations.

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