User:Inoshika/sandbox

A Probabilistic Neural Network (PNN) is a Feedforward neural network, which was derived from Bayesian network and a statistical algorithm called Kernel Fisher discriminant analysis. It was introduced by D.F. Specht in the early 1990s. In a PNN, the operations are organized into a multilayered feedforward network with four layers: PNN often use in classification problems .When an Input is present, first layer computes the distance from the input vector to the training input vectors. It produce a vector where its elements indicate how close the input is to training input. The second layer sums the contribution for each class of inputs and produce it's net output as a vector of probabilities.Finally, a compete transfer function on the output of the second layer picks the maximum of these probabilities, and produces a 1 for that class and a 0 for the other classes.
 * Input layer
 * Pattern layer
 * Summation layer
 * Output layer