Probabilistic neural network: Difference between revisions

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A '''probabilistic neural network (PNN)''' is a [[feedforward neural network]], which was derived from the [[Bayesian network]]<ref>http://herselfsai.com/2007/03/probabilistic-neural-networks.html{{dead link|date=October 2016}}</ref> and a statistical algorithm called [[Kernel Fisher discriminant analysis]].<ref>http://www.psi.toronto.edu/~vincent/research/presentations/PNN.pdf</ref> It was introduced by D.F. Specht in the early 1990s.<ref name=Specht1990>{{Cite journal | last1 = Specht | first1 = D. F. | doi = 10.1016/0893-6080(90)90049-Q | title = Probabilistic neural networks | journal = Neural Networks | volume = 3 | pages = 109–118 | year = 1990 | pmid = | pmc = }}</ref> In a PNN, the operations are organized into a multilayered feedforward network with four layers:

* Input layer

* Hidden layer